Module 1. Introduction to Data Science and Analytics

• Understanding the basics of data science and analytics
• Exploring the role of data scientists and analysts in various
• Industries Overview of d at a science process and lifecycle

Module 2. Mastering Excel

• Importing Data into Excel
• Format a worksheet, Enter a formula
• Enter a function, Create and use named ranges
• Create a simple chart, Modify data
• Insert a new worksheet, Insert rows and columns into a worksheet
• Sort and filter data, Create an Excel table
• Exploring Data with PivotTables & Essential Excel Data Analysis Functions

Module 3: Understanding Python and Advanced Python

• Basic Understanding of Python
• In-depth knowledge about Python and Libraries within it
• Techniques for data exploration and data visualization
• Using popular data visualization libraries such as Matplotlib
• Exploring Seaborn and Plotly
• Interpreting and analyzing data using visualizations

Module 4: Mastering SQL (MySQL + DB2 + MongoDB)

• Database Fundamentals (DDL, DML, DQL)
• SQL Basic Queries with Group By, Functions, Alter, String Pattern, Range
• SQL Inner, Outer, Left, Right Joins, with Subqueries
• Connecting MySQL, DB2 with Python, Importing and Exporting Data to Database
• Working with MongoDB (NoSQL Database)

Module 5: Data Preprocessing and Feature Engineering

• Understanding the importance of data preprocessing in data science
• Techniques for data cleaning, handling missing values, and handling outliers
• Feature engineering techniques for extracting relevant information from raw data

Module 6: Data Visualization and Communication

• Advanced data visualization techniques using tools such as:
  1. Tableau
  2. Power BI
  3. Dash
• Communicating data insights effectively to stakeholders
• Storytelling with data and creating impactful data visualizations