What topics are covered in the 12-hour Data Science full course?

The course introduces core data science concepts, including data analysis, machine learning fundamentals, Python-related workflows, and practical data science applications.

Does this Data Science course include machine learning concepts?

Yes. It covers foundational machine learning concepts as part of a broader introduction to the data science workflow.

How long does it take to complete the Data Science full course?

The course content runs for approximately 12 hours and can be completed at your own pace.

Free Course Image Data Science full course

Free online course Data Science full course

Duration of the online course: 11 hours and 22 minutes

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Build job-ready data science skills fast with a free online course—learn to analyze data, create models, and boost your career with hands-on practice.

In this free course, learn about

What data science is and where it’s used (business, tech, research use cases)
End-to-end data science workflow: problem framing to deployment basics
Python foundations for data science (core syntax, notebooks, key libraries)
Data wrangling with NumPy and pandas (cleaning, merging, transforming data)
Exploratory Data Analysis (EDA) and data visualization principles
Statistics essentials: probability, distributions, sampling, hypothesis testing
Supervised learning basics: regression and classification concepts
Model evaluation: train/test split, cross-validation, metrics (accuracy, RMSE, etc.)
Unsupervised learning: clustering and dimensionality reduction fundamentals
Feature engineering and preprocessing: scaling, encoding, handling missing values
Machine learning algorithms overview and when to use them (e.g., trees, KNN, SVM)
Intro to deep learning concepts and common neural network applications

About the free online course

Data science sits at the heart of modern decision-making, powering everything from personalized recommendations to smarter business forecasting. This free online course is designed for beginners who want a clear, practical path into the field without getting lost in jargon. You will learn how data science problems are framed, how insights are extracted from real-world data, and how machine learning fits into the bigger picture of artificial intelligence.

Through a guided, end-to-end learning experience, you will build confidence with the typical workflow used by data professionals: understanding the question, preparing data, exploring patterns, and turning results into actionable outcomes. Along the way, you will develop a stronger intuition for what makes data reliable, how to spot issues early, and how to think analytically when results are messy or ambiguous. The goal is not just to follow steps, but to understand why each step matters and when to apply it.

This course also helps you connect technical skills to career value. Whether you are aiming for a first role in analytics, planning a transition into machine learning, or simply adding a powerful skillset to your current job, you will gain a foundation that supports real project work. By focusing on practical reasoning and widely used methods, you will be better prepared to keep learning, build a portfolio, and speak confidently about your process in interviews or team discussions.

If you want a structured way to start in data science, this course offers a straightforward entry point: learn the essentials, practice thinking like a data scientist, and leave with knowledge you can apply immediately to your own datasets and professional challenges.

Course content

Video class: Data Science Full Course - 12 Hours | Data Science For Beginners [2023] | Edureka 11h22m

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Explore the best free online Data Science courses and build job-ready skills in Python, statistics, machine learning, data analysis, and visualization. Learn at your own pace with beginner-friendly lessons, practical projects, and expert guidance. Enroll today in free Data Science courses with a certificate and advance your career.