This course offers a comprehensive exploration of data analysis and data science techniques, equipping students with the skills to extract valuable insights from data. Covering a range of topics including data preprocessing, exploratory data analysis, statistical modeling, machine learning, and data visualization, students will learn how to manipulate data, perform statistical analyses, and build predictive models. Through hands-on projects and case studies, students will gain practical experience with tools such as Python, R, and libraries like Pandas, NumPy, scikit-learn, and matplotlib. By the end of the course, students will be able to apply data science techniques to real-world problems, making data-driven decisions and communicating their findings effectively.


  1. Introduction to Microsoft Excel
  2. Introduction to Microsoft PowerBI
  3. Introduction to MySql
  4. Introduction to Python
  5. Introduction to Machine Learning

Target Audience

This course is designed for anyone interested in data science and analytics.


Certificate of Completion

Duration Training Date Training Mode

16 Sessions


Next 8-week session Starts April