What You’ll Learn

This course provides an introduction to data analytics using Python, equipping you with the fundamental skills needed to analyze, visualize, and interpret data. You will learn how to use Python and its powerful libraries to perform data analysis tasks such as data cleaning, manipulation, and visualization. Key topics covered include:

• Introduction to data analytics and Python programming

• Data manipulation and analysis using Pandas

• Data visualization techniques with Matplotlib and Seaborn

• Data cleaning, handling missing values, and preprocessing

• Exploratory Data Analysis (EDA) to identify patterns and insights

• Introduction to basic statistics for data analysis

• Working with real-world datasets and solving practical problems

• Communicating findings through reports and visualizations

• By the end of the course, you’ll be able to use Python to perform basic data analysis tasks, making it an excellent foundation for further study in data science or analytics.

​

​

​

Chapters

 

1. Introduction to Data Analytics and Python

2. Python Basics for Data Analytics

3. Data Structures and Libraries

4. Data Cleaning and Preprocessing

5. Exploratory Data Analysis (EDA)

6. Data Visualization with Matplotlib and Seaborn

7. Basic Statistical Analysis

8. Real-World Data Analysis Projects

9. Communicating Insights through Reports and Dashboards

10. Capstone Project

​

Students are required to complete 39 hours of  training.

Subject/Module Outline For Each Subject In the Program

Total Program Instruction Hours: 39 hours

Instruction Hours Entered:39 hours