Learn Datascience Online: Free Course with AI Tutor & Certificate
This free online data science course teaches you how to clean data, perform exploratory data analysis, and build machine learning models. Across 36 video lessons and about 1 hour of content, you'll master tools like Python and Pandas to analyze real-world datasets and predict trends.
What you'll learn in this Datascience course
Five concrete outcomes you'll walk away with, each mapped to modules in the curriculum below.
Understand the fundamentals of data science and its importance in various domains.
Collect and clean data using different techniques and handle missing data and outliers effectively.
Perform exploratory data analysis by visualizing data, analyzing descriptive statistics, and exploring correlation and covariance.
Preprocess data by applying encoding techniques, feature scaling, handling imbalanced data, and reducing dimensionality.
Apply feature selection techniques to identify and select relevant features for machine learning models.
Gain knowledge of various machine learning algorithms, including supervised and unsupervised learning, and evaluate model performance using appropriate metrics.
Utilize popular data science tools and libraries such as Python, R, NumPy, Pandas, Matplotlib, Jupyter Notebook, and Anaconda.
Datascience course syllabus
01 Introduction to Data Science
- Introduction to Data Science
- What is Data Science?
- Importance of Data Science
- Applications of Data Science
02 Data Collection and Cleaning
- Data Collection Methods
- Data Cleaning Techniques
- Handling Missing Data
- Dealing with Outliers
- Data Transformation
03 Exploratory Data Analysis
- Introduction to Exploratory Data Analysis
- Data Visualization Techniques
- Descriptive Statistics
- Correlation and Covariance Analysis
- Data Exploration Techniques
04 Data Preprocessing
- Introduction to Data Preprocessing
- Data Encoding Techniques
- Feature Scaling
- Handling Imbalanced Data
- Dimensionality Reduction Techniques
05 Machine Learning Algorithms
- Introduction to Machine Learning
- Supervised Learning Algorithms
- Unsupervised Learning Algorithms
- Evaluation Metrics for Machine Learning Models
- Model Selection and Hyperparameter Tuning
06 Understanding Supervised and Unsupervised Learning
- Definition of Supervised Learning
- Definition of Unsupervised Learning
- Key Differences Between Supervised and Unsupervised Learning
07 Feature Selection and Data Preprocessing in Machine Learning
- Definition and Purpose of Feature Selection in Machine Learning
- Definition and Purpose of Data Preprocessing in Data Science
08 CRISP-DM Model and Regularization in Machine Learning
- Steps Involved in the CRISP-DM Model for Data Mining
- Explanation of How Regularization Prevents Overfitting in Machine Learning Models
09 Data Science Tools and Libraries
- Introduction to Data Science Tools
- Python for Data Science
- R for Data Science
- Data Science Libraries
- Data Science Platforms
Real-world projects you'll work on
Practice the exact kind of work Datascience professionals do on the job.
Predictive Customer Analytics for E-commerce Giant: Leveraging machine learning algorithms and exploratory data analysis techniques to analyze customer behavior and predict future purchasing patterns for a leading global e-commerce company.
Fraud Detection and Prevention for Financial Services Leader: Implementing advanced data preprocessing techniques and supervised learning algorithms to develop a robust fraud detection system for a top multinational financial services organization.
Sentiment Analysis for Social Media Platform: Utilizing natural language processing and data visualization techniques to analyze user sentiments and trends on a popular global social media platform, enabling targeted marketing campaigns and improved user engagement.
Supply Chain Optimization for Global Logistics Firm: Applying dimensionality reduction techniques and correlation analysis to optimize supply chain operations for a major international logistics company, reducing costs and improving efficiency.
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this Datascience course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- College students looking for a data science course syllabus that covers practical tools like Python and Pandas.
- Career switchers who want to learn data science basics without paying high upfront fees.
- IT professionals aiming to add machine learning algorithms to their current skill set.
Prerequisites
- No prior data science experience is required to start this course.
- Basic familiarity with high school mathematics and statistics is helpful.
- A computer with internet access to run Jupyter Notebook and Python libraries.
How learning works on LearnTube
The structure of a bootcamp, the price of free.
AI curates your path
Our AI picks the top 1% of video content for each topic and arranges it into a structured, goal-based curriculum. No more tutorial roulette.
Learn, then get quizzed
After every lesson, your AI tutor asks you a question and gives personalised feedback on your answer, so gaps get fixed immediately.
Finish with proof
Complete the course, build the capstone project, and claim a certificate recognised by 900+ hiring partners.
A complete Datascience course: free, structured and job-focused
Start by building a predictive customer analytics model for an e-commerce giant, then expand your skills to cover the entire data lifecycle. This free data science course teaches you how to turn raw information into clear business decisions. You will begin with Data Collection and Cleaning, moving quickly into Exploratory Data Analysis and Data Preprocessing. From there, you'll tackle Machine Learning Algorithms, Understanding Supervised and Unsupervised Learning, and the CRISP-DM Model and Regularization in Machine Learning. You will also master Feature Selection and Data Preprocessing in Machine Learning to ensure your models are accurate.
You'll apply these concepts across four major hands-on projects. After predicting customer behavior, you will build a fraud detection system for a financial services leader, run sentiment analysis for a social media platform, and optimize supply chain operations for a global logistics firm. You'll use popular Data Science Tools and Libraries like Python, R, NumPy, Pandas, Matplotlib, and Jupyter Notebook to complete these tasks.
LearnTube makes studying easy by organizing top YouTube videos into a structured learning path. You'll take an AI-tutor quiz after every single lesson to check your understanding and fix mistakes instantly. The 9 modules and 36 video lessons take about 1 hour to complete. Learning is completely free, and if you want to show off your new skills to the 900+ hiring partners in our network, you can choose to add an optional paid certificate at the end.
Jobs you can target after learning Datascience
Datascience is a gateway skill for some of the fastest-growing roles in tech.
Cleans data and builds visual reports to help companies make better business decisions.
Builds and tests machine learning models to predict trends and automate complex tasks.
Designs and deploys scalable software systems that run supervised and unsupervised learning algorithms.
Typical entry-level salary ranges in India as of September 2026. Actual compensation varies by city, company and experience.
Earn a Datascience certificate employers recognise
Finish the course and claim a certificate you can share anywhere.
- Learn 100% free: every lesson, quiz and the AI tutor cost nothing
- Claim your certificate when you complete the course (an optional paid add-on)
- Recognised by 900+ hiring partners across India
- One click to share on LinkedIn and add to your resume
Why learners choose LearnTube
Real reviews from Google. You learn free, you get assessed free, and you pay only if you want the certificate.
Though I have 11 years of experience as an HRBP, the course helped me refresh my knowledge and gave me insights into new trends in the market. The modules were clear and easy to understand, and the quizzes were well designed. I have added the certificate to my LinkedIn profile.
I had a lot of doubts while learning, but the AI chatbot answered them in detail with simple summaries. The videos on the platform saved me a lot of time as I didn't have to search YouTube and watch random content.
Just earned my certificate in HR Management from LearnTube.ai! The platform is user-friendly and the assessment was a great way to validate my knowledge. Feeling proud of this accomplishment!
I enrolled in a LearnTube personalized course to get into a Data Analytics role. It helped me learn SQL in depth and gave me hands-on experience with Power BI. I attached the LearnTube certificate to my CV, it added credibility to my profile, and I'm currently in the interview process.
The interface is user-friendly and intuitive, making it easy to navigate the course. I encountered no errors during my time using the platform, which was a refreshing change from other online learning platforms.
Just cleared the Business Analyst assessment and got certified! Loved how the course simplifies big concepts like data-driven decision making into short, practical lessons. The automated quizzes kept me on track the whole time. Perfect boost for my resume!
The certificate gave me a real edge during my B.Tech. By the time I graduated, I had skills that set me apart from my peers, and the certification opened up more job opportunities. It gave me the confidence to stand out during interviews.
I manage many software projects as a General Manager and was looking for a good certification program to stay competitive. After researching many programs, I chose LearnTube and it was much better than I expected. The material is well-organized and practical, and what I liked most is the lifetime access.
Frequently asked questions
Everything learners ask before starting this Datascience course.
Is this a free data science course?
Yes, all 36 video lessons and AI-tutor quizzes are completely free. You can learn everything from data cleaning to machine learning algorithms at no cost, with an optional paid certificate available when you finish.
What is the data science course duration?
The course includes 9 modules and 36 video lessons that take about 1 hour of total watch time. Because it is entirely self-paced, you can spread the lessons out or finish them all in one afternoon.
Do I need coding experience to learn data science?
No, you do not need advanced coding skills to begin. The lessons start with an Introduction to Data Science and gradually introduce you to Python, Pandas, and machine learning concepts in a beginner-friendly way.
How is this different from watching plain YouTube videos?
LearnTube organizes curated YouTube videos into a structured data science syllabus. You will also get an AI tutor that tests your knowledge with a short quiz after every single lesson to ensure you actually understand the material.
Are data science classes still worth taking?
Yes, data skills are highly valued across almost every industry in India. Companies constantly need professionals who can handle data collection, build predictive models, and run sentiment analysis to guide their business strategies.
Will I get a data science certificate?
Yes, you can purchase an optional certificate of completion after finishing all modules and quizzes. Adding a data science certificate online to your resume or LinkedIn profile helps prove your new skills to employers.
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