Data Science Course (Self-Paced Professional Training)

The Data Science Course – Beginner to Intermediate is a structured, hands-on learning program designed for students, professionals, and career switchers who want to enter the world of data-driven decision-making.

This course introduces learners to the core concepts of Data Science, including how data is collected, cleaned, analyzed, visualized, and interpreted to solve real-world problems. You will understand the complete data science lifecycle, from raw data to actionable insights, with a strong focus on practical understanding rather than heavy theory.

The program emphasizes data analysis and visualization, helping learners interpret trends, patterns, and insights using structured approaches. You will gain exposure to essential data science concepts such as data preprocessing, exploratory data analysis (EDA), basic statistics, and business-oriented data interpretation.

Designed specifically for beginners progressing to intermediate learners, this course builds confidence in working with data and prepares you for advanced learning paths such as Machine Learning, Artificial Intelligence, Business Analytics, or Data Engineering.

By the end of the course, learners will be equipped with industry-relevant data science fundamentals, practical analytical thinking, and a recognized course completion certificate to support career growth.

What You Will Learn

• Fundamentals of Data Science and analytics

• Understanding structured and unstructured data

• Data cleaning and preprocessing concepts

• Exploratory Data Analysis (EDA)

• Basic statistical concepts for data interpretation

• Data visualization and storytelling with data

• Real-world use cases of Data Science

• Career paths in Data Science and Analytics

Learning Outcomes

After completing this course, you will be able to:

• Understand the complete data science workflow

• Analyze and interpret datasets effectively

• Apply statistical thinking to data problems

• Visualize data insights for business decisions

• Build a strong foundation for advanced Data Science and AI topics

• Confidently pursue entry-level data roles or upskilling opportunities