Become A Data Analyst - Tableau | Python | Power Bi | Sql



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.40 GB | Duration: 10h 22m

Mastering Analytics: From Data Visualization to Business Intelligence


What you'll learn
Understand the role and responsibilities of a Data Analyst in various industries.
Gain a foundational understanding of key data analysis and visualization tools, including Tableau, Python, Google Data Studio, and Power BI.
Learn to set up Tableau Public Desktop and navigate its interface for data analysis and visualization projects.
Master the process of connecting to various data sources within Tableau and performing data joins on related datasets.
Acquire the skills to clean and preprocess data in Tableau to ensure accuracy and relevance in analysis.
Develop the ability to create compelling data visualizations and dashboards in Tableau that tell a story or reveal insights.
Install Anaconda and understand the differences between Anaconda and Miniconda for managing Python environments.
Get familiar with Jupyter Notebook as an interactive computational environment for Python programming.
Understand the basics of Python programming, including expressions, statements, data types, and variables.
Learn to work with Python data structures such as lists, tuples, dictionaries, and sets for efficient data manipulation.
Master Python's control structures, including conditional statements and loops, for complex data analysis tasks.
Explore the use of Python functions and modules to organize and reuse code effectively.
Dive into data analysis with Python using the Pandas library for data manipulation and analysis.
Practice data cleaning techniques in Python to prepare datasets for analysis.
Learn the fundamentals of data visualization in Python
Gain an introductory understanding of Google Data Studio for creating interactive reports and dashboards.
Explore the process of connecting Google Data Studio to different data sources and importing data.
Learn to create and customize various types of visualizations in Google Data Studio, including charts, tables, and geo maps.
Understand the basics of Power BI, including setting up Microsoft 365 and installing Power BI Desktop.
Master data transformation and modeling in Power BI to create compelling data visualizations.
Learn the process of publishing reports to Power BI Service and building interactive dashboards.
Acquire foundational knowledge in SQL for querying and analyzing data stored in relational databases.
Understand MySQL database concepts, installation, and the use of MySQL Workbench for database management.
Learn advanced SQL techniques for data analysis, including table joins, subqueries, and the use of aggregate functions to summarize data.
Requirements
No prior experience in data analysis or programming is required. This course starts with foundational concepts, making it accessible for beginners.
Basic Computer Literacy: Comfort with operating computers and navigating the internet will be beneficial.
Familiarity with Excel: While not mandatory, basic knowledge of Excel or any spreadsheet software can be helpful as it introduces concepts like data manipulation and simple formulas, which are foundational to data analysis.
A Computer: A laptop or desktop with internet connectivity is essential for accessing course materials, video lectures, and software used in the course.
Software Installation: You will need to install specific software such as Tableau Public (free version), Anaconda for Python, Google Data Studio (free web-based tool), and Microsoft Power BI Desktop (free version). Installation guides and resources will be provided in the course.
Web Browser: A modern web browser (like Chrome, Firefox, or Edge) will be required to access Google Data Studio and other online resources.
Description
Embark on a transformative journey to become a skilled Data Analyst with our comprehensive course: "Become a Data Analyst - Tableau | Python | Google Data Studio | BI | SQL." This meticulously designed course aims to equip you with the essential tools and techniques of data analysis, visualization, and business intelligence, ensuring you emerge as a proficient data analyst ready to tackle real-world challenges.Course Overview:Introduction to Data Analysis: Dive into the world of data analysis by understanding the pivotal role of a Data Analyst. Explore the responsibilities, tools, and the impact of data analysis in driving business decisions and strategies.Mastering Tableau for Data Visualization: Unlock the power of Tableau, the leading visualization tool, starting from setup to advanced data manipulation techniques. Learn through hands-on exercises on connecting data sources, cleaning data, and crafting compelling stories through visualizations.Python and Jupyter Notebook for Data Analysis: Venture into Python programming, a cornerstone for any Data Analyst. From basic syntax to complex functions, this section covers it all, including an in-depth exploration of Jupyter Notebook for executing Python code in an interactive environment.Exploring Google Data Studio: Navigate through Google Data Studio to create dynamic reports and dashboards. Gain proficiency in importing data, connecting to various data sources, and visualizing data to uncover insights.Analyzing Data with Power BI: Step into the world of Power BI, a premier business intelligence platform. Learn to install, connect to data, transform datasets, and visualize insights, culminating in the publication of reports and dashboards.SQL and MySQL for Data Management and Analysis: Build a strong foundation in SQL and MySQL, from database concepts to advanced data analysis techniques. Master table joins, aggregate functions, and the art of querying databases to extract meaningful information.Advanced Data Analysis Techniques: Elevate your skills with advanced SQL techniques, including inner, left, right, and self joins, subqueries, and the use of aggregate functions to perform complex data analysis.Throughout this course, you'll engage in practical exercises and projects, applying what you've learned in real-world scenarios. Whether you're new to data analysis or looking to enhance your skills, this course offers a path to mastery across the most powerful data analysis and visualization tools available today.Prepare to transform data into actionable insights and propel your career forward as a Data Analyst. Join us on this journey to mastering the art and science of data analysis.
Overview
Section 1: Introduction to Data Analysis
Lecture 1 Introduction
Lecture 2 What is a Data Analyst
Lecture 3 The role and responsibilities of a Data Analyst
Lecture 4 Overview of Data Analysis Tools
Section 2: Introduction to Tableau and Setup
Lecture 5 What is Tableau
Lecture 6 Tableau Public Desktop
Lecture 7 Tableau Public Desktop Overview: Part 1
Lecture 8 Tableau Public Desktop Overview: Part 2
Lecture 9 Tableau Online
Lecture 10 Tableau Data Sources
Lecture 11 Tableau File Types
Section 3: Data Analysis and Visualization with Tableau
Lecture 12 Connecting to a data source
Lecture 13 Join related data sources
Lecture 14 Join data sources with inconsistent fields
Lecture 15 Data Cleaning
Lecture 16 Exploring Tableau Interface
Lecture 17 Reordering Visualization
Lecture 18 Change Summary
Lecture 19 Split text into multiple columns
Lecture 20 Presenting data using stories
Section 4: Python and Jupyter Notebook Setup
Lecture 21 What is Jupyter Notebook
Lecture 22 Anaconda vs Miniconda
Lecture 23 Installing Anaconda on a Mac
Lecture 24 Verify Anaconda installation on mac
Lecture 25 Installing Anaconda on Windows
Lecture 26 Verify Anaconda on Windows
Lecture 27 What is Anaconda Navigator
Lecture 28 Introduction to Anaconda Navigator
Lecture 29 Anaconda Navigator Overview
Lecture 30 Installing Jupyter Notebook using Anaconda
Lecture 31 How to start Jupyter Notebook Server
Lecture 32 Creating a new notebook
Section 5: Python Fundamentals
Lecture 33 What is Python
Lecture 34 Python Expressions
Lecture 35 Python Statements
Lecture 36 Python Comments
Lecture 37 Python Data Types
Lecture 38 Casting Data Types
Lecture 39 Python Variables
Lecture 40 Python List
Lecture 41 Python Tuple
Lecture 42 Python Dictionaries
Lecture 43 Python Operators
Lecture 44 Python Conditional Statements
Lecture 45 Python Loops
Lecture 46 Python Functions
Section 6: Data Analysis with Python
Lecture 47 Kaggle Data Sets
Lecture 48 Tabular Data
Lecture 49 Exploring Pandas DataFrame
Lecture 50 Manipulating a Pandas DataFrame
Lecture 51 What is data cleaning
Lecture 52 Basic data cleaning
Lecture 53 What is data visualization
Lecture 54 Visualizing Qualitative Data
Lecture 55 Visualizing Quantitative Data
Section 7: Data Analysis and visualization with Google Data Studio
Lecture 56 What is Google Data Studio
Lecture 57 How to access Google Data Studio
Lecture 58 Exploring Google Data Studio Interface
Lecture 59 Data sources and connectors
Lecture 60 Importing data into data studio
Lecture 61 Connecting to sample data source
Lecture 62 Creating data visualization
Lecture 63 Importing data into Googlesheets
Lecture 64 Connecting to Googlesheets
Lecture 65 What are dimensions
Lecture 66 What are metrics
Lecture 67 Data refresh frequency
Lecture 68 Exploring edit and view modes in reports
Lecture 69 Creating a Pie Chart
Lecture 70 Creating a Bar Chart
Lecture 71 Adding a table to report
Lecture 72 Sorting data in columns
Lecture 73 Add bars to table metrics columns
Lecture 74 Creating a time series chart
Lecture 75 Customizing a time series chart
Lecture 76 Creating a Geo Chart
Lecture 77 Creating calculated fields
Lecture 78 Data cleaning using calculated fields
Lecture 79 Control Filters
Lecture 80 Adding a date range control
Lecture 81 Formatting your dashboard
Section 8: Analyzing Data and Visualization with Power BI
Lecture 82 What is Power BI
Lecture 83 Microsoft 365 Setup
Lecture 84 Exploring Microsoft 365
Lecture 85 Installing Power BI Desktop
Lecture 86 Exploring Power BI Desktop Interface
Lecture 87 Connecting to data
Lecture 88 Transforming Data
Lecture 89 Data Modelling
Lecture 90 Visualizing Data
Lecture 91 Publishing reports to Power BI Service
Lecture 92 Building a dashboard
Lecture 93 Collaborating and sharing
Section 9: Introduction to MySQL and Setup
Lecture 94 What is SQL
Lecture 95 What is MySQL
Lecture 96 Database Concepts
Lecture 97 Installing MySQL (Windows)
Lecture 98 Installing MySQL (Mac )
Lecture 99 What is MySQL Workbench
Lecture 100 Installing MySQL Workbench (Mac)
Lecture 101 MySQL Data Types
Lecture 102 Overview of using MySQL and SQL for Data Analysis
Lecture 103 Introduction to Databases
Section 10: Data Analysis with SQL
Lecture 104 Introduction to Table Joins
Lecture 105 Analysing data using SQL INNER Join
Lecture 106 Analysing data using SQL LEFT Join
Lecture 107 Analysing data using SQL RIGHT Join
Lecture 108 Analysing data using SQL SELF Join
Lecture 109 Analysing data using Sub Query
Lecture 110 Analysing data using SQL Nested Sub Query
Lecture 111 Introduction to Aggregate functions
Lecture 112 Analysing data using SQL AVG Aggregate Function
Lecture 113 Analysing data using SQL COUNT Aggregate Function
Lecture 114 Analysing data using SQL SUM Aggregate Function
Lecture 115 Analysing data using SQL MIN Aggregate Function
Lecture 116 Analysing data using SQL MAX Aggregate Function
Lecture 117 Aggregate functions in SQL GROUPBY Clause
Lecture 118 Aggregate functions in SQL HAVING Clause
Lecture 119 Filtering data with the WHERE Clause
Lecture 120 Sorting data with ORDER BY Clause
Individuals looking to pivot into a data-driven career will find this course an invaluable stepping stone. Whether you're transitioning from a non-technical role or seeking to enter the tech industry, our comprehensive curriculum will guide you through the essentials of data analysis, visualization, and business intelligence tools.,Aspiring data analysts with little to no prior experience in the field are prime candidates for this course. We start with the basics, ensuring that learners gain a solid foundation in data analysis concepts and tools, making the course ideal for those who are starting their journey in data analytics.,College students or recent graduates in fields such as business, economics, computer science, or any other discipline who wish to enhance their data analysis skills will benefit significantly. This course can complement your academic knowledge, providing practical, hands-on experience with tools and techniques used in the industry.,Working professionals in roles that involve data handling, reporting, or decision-making, such as business analysts, marketing professionals, and project managers, will find the course content directly applicable to their work. Enhancing your data analysis skills can lead to improved job performance, opportunities for advancement, or even a specialisation shift within your career.,Entrepreneurs who need to make data-driven decisions to grow their business will benefit from learning how to analyze data effectively. This course will empower you to understand your business data better, identify trends, and make informed decisions.,Individuals with a keen interest in data, technology, and analytics, looking to explore new skills or understand the world of data analysis better, will find the course engaging and enlightening. It's an excellent opportunity for personal growth and intellectual stimulation.
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AWS Machine Learning: From Basics To Hands-On Projects



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.14 GB | Duration: 2h 21m

Master AWS Machine Learning with comprehensive lessons and hands-on projects to transform data into actionable insights.


What you'll learn
Introduction to AWS Machine Learning: Understand the fundamentals of AWS Machine Learning and its key features.
Data Sourcing and Preparation: Learn the lifecycle of AML, from data ingestion to model deployment.
Managing Data Quality and Variables: Address data quality issues, including handling invalid values.
Hands-On Data Insights: Engage in practical exercises to create and manage data sources.
Building and Evaluating ML Models: Develop and fine-tune machine learning models using AWS's advanced settings.
End-to-End ML Project Management: Master the creation, management, and evaluation of ML objects in AWS.
Requirements
Basic Knowledge of AWS Services: Familiarity with core AWS services like S3, EC2, and IAM will be beneficial.
Foundational Programming Skills: Basic knowledge of Python is recommended, as it will be used for scripting and model management.
Interest in Machine Learning: No prior experience in machine learning is required, but an enthusiasm for learning how to build ML models will enhance your experience.
Description
In the era of data-driven decision-making, mastering machine learning is a valuable skill. The AWS Machine Learning Mastery: From Basics to Hands-On Projects course is designed to take you from the fundamentals of AWS Machine Learning (AML) to practical applications. Whether you are new to the field or looking to deepen your knowledge, this course offers a structured and engaging approach to mastering AWS's machine learning services. Through step-by-step guidance, real-world examples, and hands-on exercises, you will gain the skills needed to implement powerful ML models using AWS.Section-wise Writeup:Section 1: IntroductionThis section lays the foundation by introducing you to AWS Machine Learning (AML). We begin with an overview of the platform, its capabilities, and how it integrates with other AWS services. You'll learn about the key features of AWS Machine Learning and how it simplifies the process of building, training, and deploying machine learning models. By the end of this section, you'll have a clear understanding of AML's role in modern data science.Section 2: DatasourceIn this section, we dive into the critical aspect of data sourcing, which forms the backbone of any machine learning project. We start with the Lifecycle of AML, exploring the journey from data preparation to model deployment. You'll learn how to connect to various data sources, including S3 buckets, databases, and on-premises systems. Additionally, you'll discover how to create robust data schemes within AML, setting the stage for effective model training. This section ensures you are equipped to handle the complexities of data integration in AWS.Section 3: ValueThis section focuses on the value aspect of machine learning models. We address how to manage invalid values in datasets and set up variable targets for accurate predictions. You'll gain insights into the different types of ML models available in AML and how to select the best fit for your project needs. We also cover managing machine learning objects, such as datasets, models, and batch predictions, providing a comprehensive understanding of AML's functionalities.Section 4: Datasource Hands-OnLearning by doing is crucial for mastering new skills, which is why this section emphasizes practical application. You'll engage in hands-on exercises, starting with creating data sources in AML. This includes a step-by-step walkthrough on setting up and managing data sources, followed by deeper dives into extracting insights from your datasets. By the end of this section, you'll be proficient in leveraging AWS's tools to analyze and interpret data, turning raw information into actionable insights.Section 5: ML Model Hands-OnThe final section brings everything together by guiding you through the process of building, evaluating, and deploying machine learning models. You'll explore real-world examples, create ML models, and learn how to fine-tune them using advanced settings. We also cover batch predictions, enabling you to automate the process of generating predictions for large datasets. The hands-on sessions culminate in a comprehensive overview of managing ML objects in AML, ensuring you are ready to implement these techniques in practical scenarios.Conclusion:By the end of the AWS Machine Learning Mastery: From Basics to Hands-On Projects course, you will have gained a robust understanding of AWS Machine Learning. You'll be proficient in sourcing, preparing, and analyzing data, as well as building and deploying machine learning models on AWS. This course is designed to provide you with practical skills that can be directly applied in real-world scenarios, making you a valuable asset in any data-driven organization. Whether you are looking to advance your career, transition into a new role, or simply expand your knowledge, this course provides the tools and confidence needed to succeed in the dynamic field of machine learning.
Overview
Section 1: Introduction
Lecture 1 Introduction to AWS Machine Learning (AML)
Section 2: Datasource
Lecture 2 Lifecycle of AML
Lecture 3 Connecting to Data Source in AML
Lecture 4 Creating Data Scheme in AML
Section 3: Value
Lecture 5 Invaild Value and Varible Target in AML
Lecture 6 ML Models in AML
Lecture 7 Manging ML Object in AML
Section 4: Datasource Handson
Lecture 8 Creating DataSource Handson
Lecture 9 Creating DataSource Handson Continues
Lecture 10 Example of Data Insight In AML
Lecture 11 More on Data Insight In AML
Section 5: ML Model Handson
Lecture 12 ML Model Example in Data Sources
Lecture 13 Creating ML Model Evaluating
Lecture 14 Advanced Setting In ML Model
Lecture 15 Creating ML Model for Batch Prediction
Lecture 16 Batch Prediction Result
Lecture 17 Overvies of ML Model Handson
Lecture 18 ML objects Handson in ML
Aspiring Data Scientists & Machine Learning Engineers: Individuals looking to break into the field of data science and machine learning, especially those interested in leveraging AWS's powerful ML services.,Developers & Software Engineers: Developers who wish to expand their skill set by integrating machine learning capabilities into their applications.,Data Analysts & BI Professionals: Analysts aiming to enhance their data insights using predictive modeling and machine learning.,AWS Enthusiasts & Cloud Practitioners: Individuals who are already familiar with AWS services and want to explore its machine learning capabilities.,Tech Managers & Project Leads: IT managers and project leads looking to understand the potential of AWS Machine Learning for strategic decision-making.,Students & Academics: University students, researchers, and educators who want to apply AWS ML tools in academic projects or research.
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Aws Lambda: Real-World Projects And API Integrations



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.00 GB | Duration: 3h 30m

Unlock the power of serverless computing with AWS Lambda through hands-on projects, API integrations, and automation.

What you'll learn
Setting up and deploying AWS Lambda functions in Python.
Integrating Lambda functions with API Gateway for GET and POST requests.
Automating cloud tasks using AWS Lambda and DevOps principles.
Handling data transformations like XML to JSON using serverless architecture.
Deploying, testing, and managing serverless applications on AWS.
Building real-world projects to enhance your portfolio and cloud expertise.
Requirements
Basic knowledge of Python programming.
Familiarity with AWS services (AWS account setup is recommended).
Understanding of API concepts (RESTful services).
No prior experience with AWS Lambda is required, but basic cloud knowledge is beneficial.
Description
Course Introduction:Are you ready to harness the power of AWS Lambda for serverless computing? This course is designed to take you from the basics of AWS Lambda to mastering its real-world applications. You'll dive deep into building, deploying, and integrating Lambda functions with APIs, automating tasks, and even converting data formats seamlessly. Whether you're a developer, cloud engineer, or tech enthusiast, this course provides hands-on experience to boost your cloud skills and make you proficient in serverless technology. Join us and discover how to create efficient, scalable solutions using AWS Lambda!Section 1: AWS Lambda - Implementation for Arithmetic OperationsIn this section, you'll get an introduction to AWS Lambda and its core functionalities. Starting with setting up Lambda functions in Python, you'll learn how to connect these functions to an API and handle both GET and POST requests. We'll guide you through creating Lambda functions for basic arithmetic operations, testing payloads, and ensuring smooth API integration. By the end of this section, you'll have a solid understanding of how Lambda functions work and how to leverage them to handle API requests efficiently.Section 2: Project on DevOps - Automating a Task Using AWS LambdaThis section focuses on leveraging AWS Lambda for task automation, a critical skill in the DevOps toolkit. You'll embark on a project that showcases the automation of tasks using Lambda functions and API Gateway. You'll learn how to use Python scripts to interact with APIs, upload data to S3 buckets, and automate workflows using serverless architecture. We'll cover both GET and PUT methods and their implementation to build a dynamic serverless application. By the end of this section, you'll gain hands-on experience in automating cloud tasks and deploying serverless solutions.Section 3: Project on AWS Lambda - XML to JSON ConverterIn the final section, you'll tackle a comprehensive project: converting XML data to JSON using AWS Lambda. This project emphasizes practical coding, where you'll write Python scripts to transform data formats, discuss the code structure, and explore deployment strategies on AWS. You'll learn to create and test APIs for data conversion, covering everything from code execution to deployment and testing on AWS. The project concludes with a case study that showcases the end-to-end process, allowing you to apply your knowledge to real-world scenarios.Course Conclusion:By the end of this course, you will have a thorough understanding of AWS Lambda and its capabilities in automating tasks, handling API integrations, and transforming data formats. You'll have built multiple projects that showcase your new skills, making you confident in deploying serverless solutions in various professional environments. Whether you're looking to enhance your cloud capabilities, streamline operations, or build scalable serverless applications, this course equips you with the tools and knowledge to excel in the world of AWS. Join us and transform your cloud computing skills with AWS Lambda!
Overview
Section 1: AWS Lambda: Implementation for Arithmetic Operations
Lecture 1 Introduction
Lecture 2 AWS Lambda Function in Python
Lecture 3 Connecting Lambda Function to API
Lecture 4 Creating GET Request
Lecture 5 Creating POST Request
Lecture 6 Test Payload for GET
Lecture 7 Post Requests
Lecture 8 Lambda Function
Lecture 9 Lambda Function Continue
Section 2: Project on DevOps: Automating a Task Using AWS Lambda
Lecture 10 Introduction to Project
Lecture 11 Project Overview
Lecture 12 Python Function
Lecture 13 GET Python Function
Lecture 14 GET Lambda Function
Lecture 15 GET-PUT API Gateway
Lecture 16 PUT Python Function
Lecture 17 S3 Bucket Upload Overview
Lecture 18 Lambda-S3 Working and Flow
Section 3: Project on AWS Lambada: XML to JSON Converter
Lecture 19 Introduction to Project
Lecture 20 Introduction to Project Continue
Lecture 21 Coding Introduction
Lecture 22 Code Discussion
Lecture 23 Code Execution
Lecture 24 Case Study end Result
Lecture 25 AWS Deployment
Lecture 26 AWS Deployment Continue
Lecture 27 AWS API Creation
Lecture 28 AWS API Testing
Developers looking to expand their skillset in serverless computing with AWS.,Cloud Engineers who want to automate tasks and deploy scalable solutions.,DevOps Professionals interested in leveraging AWS Lambda for automation.,Data Engineers seeking to build data transformation pipelines using serverless functions.,Tech Enthusiasts and Students eager to learn about serverless architectures and AWS integration.,Anyone interested in enhancing their cloud skills for professional growth or personal projects.
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AWS Infrastructure Automation with Terraform



Last updated 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 37m | Size: 314 MB

Learn to use instances on AWS using terraform with security groups, vpc, and subnets.

What you'll learn
Learn basic terraform
Learn basic aws vpc networking
Learn to automate Ec2 instance creation
Learn to automate security groups, vpc creation
Requirements
No terraform knowledge required
Description
This course teaches you on how to use Terraform to create any number of instances on AWS. Cloud engineers or Devops can use terraform to automate instance creation. This course show the process live, also it will show how to do it with security groups, VPC and subnets. I will show you the complete process and also include the code with this course.Students should have access to an AWS account, or you cannot follow this course. Having a bit of knowledge in AWS dashboard will help, if you have no knowledge of AWS, you may find it a bit difficult to grasp the concepts.This is really short course, and will only use basic terraform commands to create and destroy instances with a virtual private network. So i dont assume you know terraform and i wont teach you advanced terraform commands. Also for any doubts and suggestion please contact me and i will be glad to answer your questions.Also please do not forget give a review for my course as i am new here and it will motivate me to create more course like this.Alright, let's enroll for this course and gain this awesome knowledge.ThanksRabbani
Who this course is for
Devops who wants to automate AWS instances with terraform
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AWS Elastic Beanstalk: AWS CI/CD with CodePipeline & Git



Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 29m | Size: 663 MB

Streamline your software delivery with automated CI/CD pipelines using CodePipeline, and Git!


What you'll learn
How to set up a CI/CD pipeline using AWS CodePipeline.
Configuring Git for version control in a cloud environment.
Creating and managing repositories with AWS CodeCommit.
Automating build, test, and deployment processes.
Setting up notifications and manual approvals for secure deployments.
Best practices for DevOps in AWS environments.
Requirements
Basic knowledge of AWS services and cloud computing. Familiarity with Git and version control systems. No prior experience with AWS CodePipeline or CodeCommit is required. A computer with internet access to configure the development environment.
Description
In today's fast-paced software development environment, continuous integration and continuous delivery (CI/CD) are crucial for delivering robust and efficient applications. This course is designed to equip you with the fundamental skills needed to set up a full-fledged CI/CD pipeline using AWS services. Whether you are a DevOps engineer, developer, or cloud enthusiast, this hands-on course will guide you through setting up development environments, managing configurations, and automating deployment processes. By the end of this course, you will have a solid foundation in leveraging AWS CodeCommit, CodePipeline, and Git to automate your software delivery.Section 1: IntroductionThe course begins with an introduction to the basics of DevOps and its importance in modern software development. This section sets the stage for the hands-on sessions to follow, outlining the objectives of the course and the key AWS services we will utilize. You will gain a clear understanding of how continuous integration and delivery can improve your development lifecycle, making deployments faster and more reliable.Section 2: SetupSetting up your environment correctly is essential for a smooth CI/CD pipeline. In this section, you'll learn how to configure your local and development environments to ensure compatibility with AWS services. We'll cover the essentials of setting up your environment and development tools, making sure you're ready to dive into AWS CodeCommit and CodePipeline.Lecture 2: Environment Setup - Learn the prerequisites for your development setup, including installing necessary software and configuring AWS CLI.Lecture 3: Development Environment Setup - Dive deeper into setting up your IDE and version control tools to ensure a smooth workflow.Section 3: ConfigurationThis section is the heart of the course, where you'll configure your AWS services to enable continuous integration and delivery. Starting with Git setup and progressing through AWS CodeCommit, you'll learn how to create and manage repositories. You'll also configure AWS CodePipeline to automate the build, test, and deployment process. By the end of this section, you'll have a fully functional CI/CD pipeline that can handle notifications and approvals.Lecture 4: Build and Configuration Files - Understand how to create build files and manage configurations for your projects.Lecture 5: Configuring Git - Set up Git for version control and prepare it for integration with AWS services.Lecture 6: AWS Code Commit Repository - Learn how to create and manage repositories using AWS CodeCommit for your projects.Lecture 7: CodePipeline Configuration - Step-by-step guide to configuring AWS CodePipeline for automating your CI/CD pipeline.Lecture 8 & 9: Notifications for Deployment - Explore how to set up deployment notifications to keep your team informed about the pipeline status.Lecture 10 & 11: Configuring Approval - Understand the importance of manual approvals in your pipeline and how to set them up for secure deployments.Conclusion:By the end of this course, you will have a deep understanding of setting up a complete CI/CD pipeline using AWS DevOps tools. You'll be able to automate code builds, test deployments, and streamline your software delivery process, significantly reducing time-to-market. This course is designed to help you achieve faster and more reliable software releases, making you an asset to any development team looking to enhance their DevOps practices.
Who this course is for
DevOps Engineers looking to master AWS DevOps tools for automation.
Software Developers aiming to streamline their deployment processes.
IT Professionals interested in adopting DevOps practices in their organizations.
Cloud Enthusiasts wanting to expand their AWS skill set.
Students and Fresh Graduates eager to learn CI/CD pipeline automation with AWS.
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Automate Your Workflows with Generative AI



Released: 11/2024
Duration: 20m | .MP4 1280x720, 30 fps® | AAC, 48000 Hz, 2ch | 53 MB
Level: General | Genre: eLearning | Language: English

Does your workflow need a boost? Generative AI not only automates tasks but also enhances decision-making and efficiency. In this course, workflow consultant Tamera Franklin guides you through the essentials of integrating AI into your business processes. Learn to leverage generative AI capabilities and train it for your specific needs. After this course, you'll be ready to use AI to transform your daily operations and enhance your productivity.
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Associate Professional Risk Manager Aprm Certificate



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 603.36 MB | Duration: 1h 22m

Risks, Risk Management, Definitions and Concepts, Strategic, Financial, Operational, Compliance, and Reputation Risks


What you'll learn
Risk Management
Introduction to Risk Management: Definitions and Concepts
Importance of Risk Management for Organisations
Types of Risks: Strategic, Financial, Operational, Compliance, and Reputational Risks
Risk Identification: Recognising and Assessing Risks
Risk Analysis Techniques
Risk Appetite and Risk Tolerance
Risk Mitigation Strategies: Avoidance, Reduction, Transfer, and Acceptance
Risk Monitoring and Control
Enterprise Risk Management (ERM): Integrated Approach to Managing Risks Across the Organisation
Risk Management Frameworks and Standards: COSO, ISO 31000
Requirements
For a better learning experience, we suggest you to use a laptop / mobile phone / pen and paper for taking notes, highlighting important points, and making summaries to reinforce your learning.
Description
Welcome to Program: Associate Professional Risk Manager (Associate PRM Certificate) by MTF InstituteCourse provided by MTF Institute of Management, Technology and FinanceMTF is the global educational and research institute with HQ at Lisbon, Portugal, focused on business & professional hybrid (on-campus and online) education at areas: Business & Administration, Science & Technology, Banking & Finance. MTF R&D center focused on research activities at areas: Artificial Intelligence, Machine Learning, Data Science, Big Data, WEB3, Blockchain, Cryptocurrency & Digital Assets, Metaverses, Digital Transformation, Fintech, Electronic Commerce, Internet of Things. MTF is the official partner of: IBM, Intel, Microsoft, member of the Portuguese Chamber of Commerce and Industry.MTF is present in 215 countries and has been chosen by more than 620 000 students.Course Authorr. Alex Amoroso is a seasoned professional with a rich background in academia and industry, specializing in research methodologies, strategy formulation, and product development. With a Doctorate Degree from the School of Social Sciences and Politics in Lisbon, Portugal, where she was awarded distinction and honour for her exemplary research, Alex Amoroso brings a wealth of knowledge and expertise to the table.In addition to her doctoral studies, Ms. Amoroso has served as an invited teacher, delivering courses on to wide range of students from undergraduate level to business students of professional and executives courses. Currently, at EIMT in Zurich, Switzerland, she lectures for doctoral students, offering advanced instruction in research design and methodologies, and in MTF Institute Ms. Amoroso is leading Product Development academical domain.In synergy between academical and business experience, Ms. Amoroso achieved high results in business career, leading R&D activities, product development, strategic development, market analysis activities in wide range of companies. She implemented the best market practices in industries from Banking and Finance, to PropTech, Consulting and Research, and Innovative Startups.Alex Amoroso's extensive scientific production includes numerous published articles in reputable journals, as well as oral presentations and posters at international conferences. Her research findings have been presented at esteemed institutions such as the School of Political and Social Sciences and the Stressed Out Conference at UCL, among others.With a passion for interdisciplinary collaboration and a commitment to driving positive change, Alex Amoroso is dedicated to empowering learners and professionals for usage of cutting edge methodologies for achieving of excellence in global business world.Risk management is the process of identifying, assessing, and controlling potential threats to an organization. These threats, or risks, could stem from a wide variety of sources.Here are the main focuses of risk management:Identification: Finding potential risks that could affect your organization or project. This involves brainstorming, looking at past issues, and considering what might happen in the future.Assessment: Determining the likelihood of those risks happening and how severe the impact would be if they did. This helps prioritize which risks need the most attention.Control: Taking steps to reduce the likelihood of the risks happening or to minimize their impact if they do. This might involve things like putting safety procedures in place, buying insurance, or having backup plans.Why is it important?Minimizes losses: By identifying and managing risks, companies can reduce financial losses, protect their reputation, and avoid legal issues.Improves decision-making: Risk management provides a framework for making informed decisions, considering potential downsides and opportunities.Enhances resilience: It helps companies to be prepared for unexpected events and to bounce back quickly from setbacks.Increases the likelihood of success: By addressing potential problems proactively, companies can increase their chances of achieving their goals.For managers specificallyrotects their team: Managers are responsible for the safety and well-being of their team. Risk management helps them create a safe work environment and minimize potential harm.Builds trust: Employees trust managers who are prepared and take steps to protect them from risks.Improves performance: When risks are managed effectively, employees can focus on their work without worrying about potential problems.In uncertain world, risk management is more critical than ever. It's an essential skill for companies and managers who want to thrive in the face of challenges.
Overview
Section 1: Introduction
Lecture 1 Onboarding to learning process
Section 2: Associate Professional Risk Manager APRM Certificate Course
Lecture 2 Unlocking the power of Risk Management
Lecture 3 Introduction to Risk Management Definitions and Concepts
Lecture 4 Importance of Risk Management for Organisations
Lecture 5 Types of Risks
Lecture 6 Risk Identification
Lecture 7 Risk Analysis Techniques
Lecture 8 Risk Appetite and Risk Tolerance
Lecture 9 Risk Mitigation Strategies
Lecture 10 Risk Monitoring and Control
Lecture 11 Enterprise Risk Management
Lecture 12 Risk Management Frameworks and Standards
Lecture 13 Conclusion
Section 3: Interactive part
Lecture 14 Interactive Part
Lecture 15 Congratulations with finishing from MTF
No special requirements. A course for anyone who wants to build career in business and risks
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Appium 2: Interceptor Plugin (Mock API Request/Responses )



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 260.61 MB | Duration: 0h 43m

An Appium Plugin to intercept Network Traffic which allows you to modify on-going requests and responses on the fly


What you'll learn
Mocking of API calls for the Mobile App - Request JSON Body, Response JSON Body, Headers
API Dependence: Mobile applications frequently rely on external APIs that may be unreliable or subject to change. The Intercept Plugin allows you to mock API
Enhanced Test Coverage: By dynamically manipulating request and response data, you can test a broader range of conditions without needing backend
Faster Testing Cycles: Mocking APIs eliminates the need for a live server and reduces test execution time
Requirements
Appium
Java
Description
In today's complex mobile applications, testing can be challenging due to the dependency on live APIs and third-party services. Traditional testing methods often fall short when dealing with inconsistent or unavailable external services. This is where the Appium Intercept Plugin becomes essential. It allows testers to simulate and control API responses, providing a crucial mechanism for robust front-end testing.Why is the Intercept Plugin Required? The Appium Intercept Plugin is designed to address several critical issues in automated testing:Simulating Edge Cases: Testing edge cases or error scenarios often requires specific API responses. With the plugin, you can simulate diverse API behaviors (like timeouts, failures, or unusual data), which helps in validating how your application handles these scenarios.API Dependence: Mobile applications frequently rely on external APIs that may be unreliable or subject to change. The Intercept Plugin allows you to mock API responses, ensuring that your tests remain stable and consistent regardless of external API availability or behavior.Enhanced Test Coverage: By dynamically manipulating request and response data, you can test a broader range of conditions without needing multiple backend configurations. This improves the coverage and effectiveness of your tests.Faster Testing Cycles: Mocking APIs eliminates the need for a live server and reduces test execution time. This leads to faster feedback during development, which is crucial for Agile and continuous integration practices.
Overview
Section 1: Introduction
Lecture 1 Introduction (Author) and My Role in Advanced QA Engineering
Section 2: Background : Common Problems and Possible Solutions
Lecture 2 Common problems faced by the front end automation frameworks
Lecture 3 Solutions to Overcome this Challenge: Key Features and Strategies
Section 3: Appium Interceptor Plugin
Lecture 4 Outline
Lecture 5 Network Interception: How It Works
Lecture 6 Appium Interceptor Plugin Architecture: How It Works
Lecture 7 Features of the Appium Interceptor Plugin: What It Offers
Section 4: Core Concepts
Lecture 8 Installation of Appium Interceptor Plugin
Lecture 9 Activate the Appium Interceptor Plugin
Lecture 10 Integrating the Appium Interceptor Plugin into Your Existing Framework: Required
Section 5: Pre-Requisite
Lecture 11 Start the Appium with Appium Interceptor Plugin
Lecture 12 Framework-Level Changes: A Walkthrough for Integrating the Appium Interceptor Pl
Section 6: Demo
Lecture 13 Mocking API Responses to Test Different Text on Mobile App UI
Lecture 14 Mocking API Status Code 500: Testing Error Handling on the Login Screen
Section 7: Q&A
Lecture 15 Questions?
Mobile App SDET /QA/QE who wants to remove dependancies from backend servers for App Automation,SDET/QA/QE who is using Appium for Mobile App Automation
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API Testing With Postman: From Beginner To Advanced



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.76 GB | Duration: 7h 40m

Become a Postman pro and excel in API testing-from creating your first request to automation and real-world projects!


What you'll learn
Master the fundamentals of API testing using Postman.
Understand and utilize HTTP methods, status codes, and collections.
Perform data-driven testing with CSV and JSON files.
Automate API tests using Newman and integrate them into CI/CD pipelines.
Develop and test real-world API projects, such as customer data and employee management systems.
Generate HTML reports and data visualizations for detailed test analysis.
Leverage Python Flask integration for backend API testing.
Requirements
Basic understanding of HTTP protocols and web technologies. Familiarity with programming fundamentals is a plus but not required. No prior experience with Postman is necessary; this course covers everything from the ground up.
Description
Introduction:APIs are the backbone of modern software development, enabling seamless communication between applications. Whether you're a beginner or an experienced developer, mastering API testing with Postman can significantly enhance your skills in ensuring API functionality, reliability, and performance. This comprehensive course is designed to take you on a journey through the essentials of API testing using Postman, starting from the basics and progressing to advanced techniques, including data-driven testing, automation, and real-world project implementations. By the end of this course, you'll have the confidence to leverage Postman for all your API testing needs.Section-wise Writeup:Section 1: Postman Training - Beginner LevelWe kick off with the fundamentals of Postman, where you'll learn to set up your environment, navigate the intuitive Postman GUI, and make your first API requests. The lectures cover the essentials of HTTP methods, including GET and POST requests, and introduce you to creating and managing collections. You'll also dive into using variables and snippets to optimize your workflow, as well as debugging your requests efficiently. By the end of this section, you'll be equipped to perform basic API testing with ease.Section 2: Postman Training - Intermediate LevelBuilding on the basics, this section delves into intermediate concepts like advanced HTTP methods and status code verification. You'll explore data-driven testing using CSV and JSON files, making your tests more dynamic and robust. We also cover testing SOAP APIs, showcasing how to pass variables and leverage Postman's capabilities for comprehensive API validation. Additionally, you'll get hands-on experience with Newman, a command-line companion tool for Postman, allowing you to automate your API tests in a CI/CD pipeline.Section 3: Postman Training - Advanced LevelReady to take your skills to the next level? This section focuses on advanced Postman features, such as data visualization, HTML report generation, and integrating Python Flask applications for backend testing. You'll learn to create detailed visualizations of your API responses and generate HTML reports to showcase your test results. The lectures also cover advanced scripting techniques to enhance your testing capabilities, making your Postman tests not only efficient but also insightful.Section 4: Postman Project - Customer Data ManagementThis section is project-based, where you'll apply your skills to manage customer data using APIs. From setting up your Postman environment to integrating Python Flask for backend functionality, you'll develop functions to handle customer data retrieval, updates, and management. This hands-on project solidifies your understanding of API testing in a real-world scenario, emphasizing best practices in API management and data handling.Section 5: Project on Postman - Employee Management SystemIn the final section, you will work on an Employee Management System project, which covers everything from adding dependencies and creating models to handling exceptions and setting up controllers. You'll learn how to build a complete API-driven system from scratch, including CRUD operations, proper request handling, and ensuring data integrity. This project aims to simulate real-world API development and testing challenges, preparing you to handle complex tasks in your professional career.Conclusion:By the end of this course, you will have transformed from a beginner to an expert in API testing with Postman. You'll gain hands-on experience with a variety of testing scenarios, enabling you to handle API testing challenges with confidence. With skills ranging from basic requests to advanced automation and project-based implementations, you'll be ready to apply these techniques in real-world projects, ensuring robust and reliable API integrations.
Overview
Section 1: Postman Training - Beginner Level
Lecture 1 Introduction of Project
Lecture 2 Installation of Postman
Lecture 3 Understanding GUI of Postman
Lecture 4 Create First API Request
Lecture 5 Create POST Request
Lecture 6 Understanding Collections
Lecture 7 Collection Runner
Lecture 8 Understanding Varibales
Lecture 9 Snippets
Lecture 10 Create Environment and Set Variables
Lecture 11 API Testing using POSTMAN
Lecture 12 DEBUG Postman
Lecture 13 Understanding Postman
Lecture 14 Testing using Newman
Lecture 15 Testing using Newman Continue
Section 2: Postman Training: Intermediate Level
Lecture 16 Introduction of Postman Intermediate
Lecture 17 HTTP Methods and URL
Lecture 18 HTTP Method Execution
Lecture 19 HTTP Method Execution Continue
Lecture 20 Checking Status Code
Lecture 21 Data Driven Testing - CSV
Lecture 22 Json
Lecture 23 Data Driven Testing - Json
Lecture 24 API Changing
Lecture 25 API Changing Continue
Lecture 26 SOAP Web Service
Lecture 27 SOAP API Testing Using Postman
Lecture 28 Understanding SOAP UI
Lecture 29 SOAP API Passing Variables
Lecture 30 Neuman Use
Section 3: Postman Training - Advanced Level
Lecture 31 Course Introduction
Lecture 32 Visualization in Postman Part 1
Lecture 33 Visualization in Postman Part 2
Lecture 34 Visualization in Postman Part 3
Lecture 35 HTML Report Generation Part 1
Lecture 36 HTML Report Generation Part 2
Lecture 37 HTML Report Generation Part 3
Lecture 38 Python Flask
Lecture 39 Testing it using Postman
Lecture 40 Python Postman Output
Section 4: Postman Project : Customer Data Management
Lecture 41 Introduction to Project
Lecture 42 Installation of Postman
Lecture 43 Libraries
Lecture 44 Anaconda and Basics of Postman
Lecture 45 Understanding Flask and Postman
Lecture 46 Writing Function Part 1
Lecture 47 Writing Function Part 2
Lecture 48 Writing Function Part 3
Lecture 49 Writing Function Part 4
Lecture 50 Writing Function Part 5
Lecture 51 Post and Get Method
Lecture 52 Implement Get Method
Lecture 53 Update Column
Lecture 54 Output of Code
Section 5: Project on POSTMAN: Employee Management System
Lecture 55 Introduction To Project
Lecture 56 Adding Dependencies
Lecture 57 Main Class
Lecture 58 Employee Model and Repository
Lecture 59 Exception Handlers
Lecture 60 Exception Handlers Continue
Lecture 61 Controllers
Lecture 62 Controllers Continuous
Lecture 63 Properties File
Beginners who want to start their journey in API testing.,Developers looking to enhance their API testing skills.,QA Engineers aiming to automate their testing processes using Postman and Newman.,Data Analysts interested in integrating API data into their workflows.,Project Managers who want to understand the capabilities of API testing for efficient project delivery.
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Apics Cpim V8 - Module 1 : Supply Chains & Strategy



Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 832.08 MB | Duration: 2h 3m

Mastering Key Areas of CPIM Version 8 - Module 1


What you'll learn
Supply Chains
Strategy Scope and Objectives
Managing Organizational Strategy
Hierachies in Business
Risk Management
Functional & Operational Strategies
Environments ,Types and Layouts
Performance Monitoring & KPIs
Requirements
Eagerness to learn about Supply Chain
Description
Important Notice Before Enrolling:This course is designed as a supplement and does not replace studying official materials from the certification provider. It is not endorsed by the certification vendor, and does not include official study materials or a voucher for the certification exam.Who Should Attend This Course1. CPIM AspirantsIdeal for those preparing for the CPIM certification.Provides a strong foundation in key CPIM topics.2. Supply Chain ProfessionalsPerfect for individuals wanting practical supply chain skills.Enhances efficiency in inventory and production roles.3. Budget-Conscious LearnersFor those who may not be able to invest in the full CPIM program.This course provides a concise overview of essential CPIM topics.BenefitsLearn critical insights and best practices in supply chain management.Strengthen your professional skill set with high-impact content at a fraction of the cost.CPIM Module 1 - OverviewFocus on Strategic Objectives: This module explores how leaders establish long-term strategies to achieve organizational goals.•Supply Chain & Operations Strategies: An introduction to supply chain management, followed by a deep dive into business strategies for competitive advantage.•Strategic Alignment: Emphasizes aligning operational goals with broader strategic priorities, even if you're not directly responsible for strategy creation.Detailed Summaryarticipants are introduced to the strategic level of supply chain management. Here, the emphasis is on aligning organizational goals with operational capabilities. This includes setting a strategic course and exploring how business and operations strategies together create lasting competitive advantages. This module emphasizes understanding strategic drivers and aligning competencies with long-term objectives to better contribute to organizational success.WHY CPIM ?There are several benefits to getting APICS CPIM (Certified in Planning and Inventory Management) certified:Enhanced Knowledge: The APICS CPIM certification provides a comprehensive understanding of production and inventory management principles, tools, and techniques. This knowledge can help professionals to make informed decisions, improve operations, and increase efficiency.Career Advancement: APICS CPIM certification is recognized globally, and it demonstrates a commitment to professionalism and excellence in the field of production and inventory management. It can open up new career opportunities and can help individuals to advance in their careers.Increased Earning Potential: According to the APICS 2021 Supply Chain Compensation and Career Survey, professionals with an APICS CPIM certification earn on average 12% more than those without the certification.Competitive Edge: The APICS CPIM certification sets professionals apart from others in the field, and it can give them a competitive edge in the job market.Industry Recognition: The APICS CPIM certification is recognized by industry professionals, employers, and supply chain organizations worldwide. It signifies a commitment to best practices and continuous improvement in production and inventory management.Overall, getting APICS CPIM certified can help professionals to improve their knowledge, advance their careers, increase their earning potential, and gain a competitive edge in the job market.As per APICS data published only 60-70% of students pass the exam every year. That is after allowing multiple retakes. This means less than 50% of students are passing the exam on the first attempt. Since the retake cost is huge around 400 dollars, clearing it on the first attempt is very crucial. ( See the promo video for a detailed explanation of this )Here's what Udemy students are saying - About "CPIM( Certified in Planning & Inventory Mgmt ) Preparation""The explanation is simple yet easy to understand. Now i know what to do before cpim " - Nor"I am taking this course because my coworker- a supply chain manager- suggested it to me. After a few changes to the course I had to update my review. I realize in my current job that I am exposed to a lot of the content in the class. So, this was helpful and meaningful to me." - Cathy "Very Good Course. I didn't find similar course anywhere on Udemy or other places " - Aditi"The course was really great! Easy to understand and very interesting. The instructor was very clear in his approach and precise."- Eric"Highly Informative. This content is not available anywhere else." - Akash "Must do course by CPIM aspirants." - Sachin"Really comprehensive and the lecturer designs the course in an innovative way. Would recommend."- Dionne"The instructor is friendly and engaging, and course well thought out and comprehensive" - Angel PSign Up Today
Overview
Section 1: Introduction
Lecture 1 Knowing the Instructor
Lecture 2 Best Practices To Understand Course Content
Lecture 3 Course Navigation
Section 2: CPIM Version 8 Overview
Lecture 4 Who Should Attend the Course
Lecture 5 CPIM Content Overview
Lecture 6 Supply Chains & Strategy - Overview
Section 3: Supply Chain , Environment & Strategy
Lecture 7 Supply Chain
Lecture 8 Manufacturing & Planning Control
Lecture 9 Strategic Hierarchy
Lecture 10 Well Crafted Business Strategy
Lecture 11 PESTEL Analysis
Lecture 12 External Factors Affecting Supply Chain
Lecture 13 Five Forces of Frame Work
Lecture 14 Bargaining Power
Lecture 15 Industry Attractiveness
Lecture 16 Product Life Cycle
Supply Chain Professionals,Professionals Planning to appear for CPIM Exam
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