Learn Data Wrangling & Feature Engineering Online: Free Course with AI Tutor & Certificate
For data enthusiasts and aspiring analysts, this free course teaches you how to clean and prepare raw datasets for machine learning. Across 11 modules and about 1 hour of video, you'll master data transformation and feature engineering basics. You'll finish ready to tackle complex datasets.
Data Wrangling & Feature Engineering course syllabus
01 Introduction to Data Wrangling
02 Data Cleaning Techniques
- Handling Missing Data
- Removing Duplicates
- Data Type Conversion
- Dealing with Outliers
- Data Normalization
03 Data Transformation
- Introduction to Data Transformation
- Scaling and Standardization
- Encoding Categorical Variables
- Log Transformation
- Binning and Discretization
04 Feature Engineering Basics
- What is Feature Engineering?
- Importance of Feature Engineering
- Feature Selection Techniques
- Creating New Features
05 Advanced Feature Engineering
- Interaction Features
- Polynomial Features
- Time-based Features
- Text Feature Extraction
- Feature Importance Analysis
06 Data Integration and Aggregation
- Merging Datasets
- Concatenating Data
- Grouping and Aggregating Data
- Pivot Tables and Cross-tabulation
- Handling Time Series Data
07 Data Wrangling with Python
- Introduction to Pandas
- DataFrames and Series
- Data Manipulation with Pandas
- Data Cleaning with Pandas
- Advanced Pandas Techniques
08 Data Wrangling with R
- Introduction to Tidyverse
- Data Frames and Tibbles
- Data Manipulation with dplyr
- Data Cleaning with tidyr
- Advanced Tidyverse Techniques
09 Data Visualization for Wrangling
- Importance of Data Visualization
- Basic Plotting Techniques
- Visualizing Data Distributions
- Identifying Patterns and Anomalies
- Advanced Visualization Tools
10 Case Studies in Data Wrangling
- 1 Real-world Data Wrangling Examples
- 1.1 Diverse Industry Applications|Presents examples of data wrangling across different industries and sectors.
- 1.2 Success Stories in Data Wrangling|Reviews case studies where effective data wrangling led to significant insights.
- 1.3 Lessons from Data Wrangling Failures|Analyzes instances where data wrangling did not go as planned and the takeaways from those experiences.
- 2 Common Challenges and Solutions
- 2.1 Identifying Data Wrangling Challenges|Discusses common issues faced during the data wrangling process.
- 2.2 Strategies for Overcoming Challenges|Presents solutions and best practices for addressing data wrangling challenges.
- 2.3 Tools and Techniques for Complex Problems|Introduces advanced tools and techniques for solving complex data wrangling problems.
- 3 Industry-specific Data Wrangling
- 3.1 Sector-based Data Wrangling Techniques|Explores how data wrangling techniques vary across different sectors.
- 3.2 Case Studies by Industry|Presents in-depth case studies of data wrangling in specific industries.
- 3.3 Adapting Wrangling Methods to Industry Needs|Discusses how to tailor data wrangling approaches to meet the unique requirements of various sectors.
- 4 Lessons Learned from Case Studies
- 4.1 Key Takeaways from Real-world Projects|Summarizes the most important lessons learned from data wrangling case studies.
- 4.2 Best Practices Derived from Experience|Compiles best practices that have emerged from real-world data wrangling experiences.
- 4.3 Applying Lessons to Future Projects|Discusses how to apply these lessons to improve future data wrangling efforts.
11 Best Practices in Data Wrangling
- 1 Documentation and Reproducibility
- 1.1 Importance of Documentation|Explains why thorough documentation is crucial in data wrangling.
- 1.2 Tools for Documenting Data Wrangling Processes|Introduces tools that can help in creating clear and comprehensive documentation.
- 1.3 Ensuring Reproducibility|Discusses practices that ensure data wrangling processes can be replicated and verified.
- 2 Efficient Data Wrangling Workflows
- 2.1 Designing Effective Workflows|Covers the principles
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this Data Wrangling & Feature Engineering course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- Aspiring data scientists who need to learn how to prepare raw datasets for machine learning models.
- Data analysts in India looking to speed up their data cleaning workflows using Python or R.
- Software developers transitioning into data roles who want to understand feature engineering basics.
- Students building data portfolios who need practical experience with data transformation.
Prerequisites
- Basic familiarity with programming concepts (like Python or R) is recommended before starting.
- A general understanding of what data analysis or machine learning entails.
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 Data Wrangling & Feature Engineering course: free, structured and job-focused
For data science beginners and analysts looking to refine their skills, this course teaches the exact steps to prepare messy data for analysis. You'll start with an Introduction to Data Wrangling before moving into core Data Cleaning Techniques and Data Transformation. Raw data is rarely ready to use out of the box, so we'll show you how to handle missing values and outliers effectively.
As you progress, the curriculum covers Feature Engineering Basics and Advanced Feature Engineering. You'll learn to create new variables that improve machine learning model accuracy. The course also includes dedicated modules on Data Wrangling with Python and Data Wrangling with R, giving you a chance to see how different programming languages handle data preparation. We wrap up with Data Visualization for Wrangling and practical Case Studies in Data Wrangling to cement your new skills.
LearnTube makes mastering these concepts simple. We take the best YouTube video lessons and organize them into a structured path. After every video, an AI tutor tests your knowledge with a quick quiz to ensure you actually understand the material. The entire learning experience is completely free. If you want to show off your new skills to employers, you can opt for a paid certificate at the end. By the time you reach Best Practices in Data Wrangling, you'll be ready to process real-world datasets with confidence.
Jobs you can target after learning Data Wrangling & Feature Engineering
Data Wrangling & Feature Engineering is a gateway skill for some of the fastest-growing roles in tech.
Cleans and interprets data to help companies make informed business decisions.
Builds predictive models and engineers features from raw data sources.
Designs and deploys scalable data pipelines and machine learning algorithms.
Constructs and maintains the systems that collect and store large datasets.
Typical entry-level salary ranges in India as of September 2026. Actual compensation varies by city, company and experience.
Earn a Data Wrangling & Feature Engineering 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 Data Wrangling & Feature Engineering course.
How does this differ from watching plain YouTube tutorials?
LearnTube organizes scattered videos into a clear, 11-module path. Instead of just passively watching, you'll answer AI-generated quizzes after every lesson to test your understanding. This structure keeps you focused and ensures you actually retain the data cleaning concepts.
What software do I need installed for this course?
You don't strictly need any software installed to watch the 61 video lessons. However, having Python or R installed on your computer will help you practice the coding concepts covered in the data wrangling modules.
Do I need prior coding experience to take this?
Yes, a basic understanding of programming is highly recommended. The course covers data wrangling with Python and R, so knowing fundamental coding concepts will make it much easier to grasp data transformation and feature engineering techniques.
What job roles can this training help me get?
This training prepares you for entry-level data roles. You can pursue positions like Data Analyst, Junior Data Scientist, or Data Engineer. These roles typically offer starting salaries between ₹3.5 LPA and ₹8.0 LPA in India.
Is this data wrangling course completely free?
Yes, the entire learning experience is completely free. You get full access to all 61 video lessons and AI quizzes at no cost. You only pay if you decide to purchase the optional certificate upon completion.
How long does it take to learn feature engineering?
This specific course contains about 1 hour of video content spread across 11 modules. If you complete the quizzes and practice the data cleaning techniques on your own, you can easily finish it within a weekend.
Is this a self-paced learning program?
Yes, this course is entirely self-paced. You can log in and learn at any time that suits your schedule. The AI tutor and quiz system are available 24/7, making it easy to study around your existing commitments.
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