Level: Beginner
🤖 Machine Learning Classification with Python and Scikit Learn
Learn classification algorithms including Logistic Regression, KNN, Naive Bayes, Decision Trees, Random Forests, and SVM by building real machine learning models with Python.
5.0
3.6k+ learners
Duration
0 min
Learners
3.6k+ Enrolled Students
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Includes
• Expert Designed Curriculum
• Doubt Clearing Session
• Forever Community Access
After this course, you can
Train classification models
Evaluate model performance
Compare ML algorithms
Solve real prediction tasks
Course Curriculum
Expand or explore the full learning path.
Lessons
Start here after enrolling. These lessons form the core learning path for the course.
Predicting a Category vs Predicting a Number
A Tour of Real Classification Problems
Features, Labels, and the Training Data That Teaches the Machine
What a "Decision Boundary" Is, Drawn in Plain Pictures
The Train/Test Split, and Why You Never Grade a Student on the Exact Questions They Studied
K-Nearest Neighbors: You Are the Company You Keep
Choosing K, Measuring Distance, and the "Curse of Dimensionality"
Naive Bayes: A Little Probability, and Why "Naive" Is Secretly a Compliment
Building a Spam Filter with Naive Bayes, Start to Finish
Logistic Regression: Regression's Cousin That Answers Yes-or-No Questions
The Sigmoid Curve, Decision Thresholds, and Reading What the Model Learned
Decision Trees: A Flowchart the Machine Draws for Itself
How a Tree Decides Where to Split (Gini and Entropy, Without the Scary Math)
Overfitting, Pruning, and the Tree That Memorized Instead of Learning
Random Forests: Why a Crowd of Okay Trees Beats One Show-Off Tree
Bagging and Feature Randomness: The Trick That Keeps the Crowd Diverse
Feature Importance: Asking the Forest What Actually Mattered
Gradient Boosting: Learning From Your Last Mistake, One Small Tree at a Time
XGBoost and LightGBM: Why These Names Show Up on Every Leaderboard
Tuning a Boosted Model Without Letting It Overfit
Support Vector Machines: Finding the Widest Street Between Two Classes
The Kernel Trick: Bending Space to Separate Things a Straight Line Can't
SVM vs Boosted Trees: When to Reach for Which
Why Accuracy Lies: Precision, Recall, and the Confusion Matrix
The Precision vs Recall Tradeoff, and Picking a Threshold on Purpose
ROC Curves and AUC Explained Without the Textbook Fog 🌫️
Imbalanced Classes: When 99% Accuracy Actually Means You Failed
Cross-Validation: Comparing Models Without Fooling Yourself
A Practical Decision Guide: Which Algorithm for Which Situation
Live Session Content
This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.
Post Session Study Material
This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.
Requirements
What you should have before starting the course.
Basic Python programming knowledge
Understand ML fundamentals
Familiarity with data preprocessing
A computer with Python installed
Tools you are going to use
Scikit-learn
Python
Pandas
NumPy
Matplotlib
Jupyter
Learn From Expert Instructor
Meet the mentors leading the live sessions.
Aarav Sharma
Senior Frontend Engineer, StudioLabs
Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.
LinkedIn
Ananya Mehta
Design Technologist, CraftLabs
Ananya blends design and code to help learners ship portfolio-ready projects.
LinkedIn
Kabir Sayed
Frontend Mentor, PixelWorks
Kabir focuses on clean code, accessibility, and practical frontend delivery.
LinkedInYou should join this course if you
Students & Fresh Graduates
Build a strong portfolio
Learn from live mentors
Get feedback on your work
Working Professionals
Upgrade frontend skills
Ship real projects
Join a peer community
Career Switchers
Structured learning path
Hands-on practice
Guided sessions
Freelancers & Creators
Build client-ready sites
Improve delivery speed
Learn modern workflows
What you will get after completing this course
Receive an official course completion certificate
Earn skill-focused feedback from mentors
Showcase your project in the Shattak community
Access lifetime notes and references
Stay connected with instructors for guidance
Completion bonus
Certificate access, community showcase, and lifetime mentor guidance.
Hear From Learners Who've Taken This Course
Honest feedback from learners who completed the live sessions.
4.8
24
Clear structure, solid examples, and a fast pace that keeps you engaged.
Riya Jain
B.Tech, NIT Trichy
4.6
18
Practical sessions with feedback that helped improve my portfolio.
Kabir Singh
Frontend Intern, PixelWorks
4.9
12
Loved the structure and the live walkthroughs.
M
Meera Patel
Design Graduate
Join Our Community, Ask Questions
Frequently Asked Questions
Students, working professionals, and career switchers who want to build job-ready web projects.
Basic familiarity with HTML or CSS is helpful, but the course includes beginner-friendly guidance.
Yes, recordings are shared after each live session.
Mentors provide live feedback and follow-up notes during the sessions.
Yes, you can ask questions in the community group and during live office hours.
Shattak courses are primarily self-paced and may include lessons, recordings, assignments, projects, and additional learning resources. Live sessions may also be conducted based on community demand.
Yes. If a live session is conducted for your course, you can access the recording and revisit the content at your own pace.
Yes. Shattak has a learning community where you can ask questions, interact with other learners, share your progress, and get guidance from mentors and peers.
Not always. Each course clearly mentions its requirements and the level of experience needed. Many courses are designed for complete beginners.
Yes. You can earn a course completion certificate after completing the required learning materials and submitting the required assignments or projects.
Yes. You can add your certificate to your LinkedIn profile, resume, portfolio, and other places where you want to showcase your learning and achievements. You may also use it for academic or professional purposes where applicable.
All Shattak courses are free to enroll in and start learning. After completing the course and earning your certificate, you can choose how much to pay from ₹0 to ₹10,000. Pay what you feel the learning experience was worth, with no questions asked.
You can explore courses by browsing different topics, skills, categories, or career paths. Each course page provides information about what you will learn, requirements, curriculum, and completion benefits.
Yes. Before enrolling, you can explore the course overview, curriculum, learning outcomes, requirements, and other details to understand what the course offers.
Simply open the course page and click Enroll. All courses are free to enroll in, so you can start your learning journey without paying upfront.
After enrolling, you will be redirected to your course workspace. From there, you can access your lessons and follow the learning path step by step.
Most courses allow you to learn at your own pace. However, some assignments, live sessions, or certification requirements may have specific deadlines.
Depending on the course, you may get access to: • Self-paced lessons • Live sessions based on community demand • Session recordings • Assignments and hands-on projects • Bonus learning resources • Mentor and peer community support • Doubt-clearing and guidance • Course completion certificates
You can ask questions through the learning community and connect with other learners. Depending on the course, you can also receive guidance from mentors and peers.
After completing the required lessons, assignments, and other course requirements, you can submit your work for certification. Once certified, you can access and share your certificate.
If you are an industry professional or expert and want to teach on Shattak, you can apply to become a mentor and create a course or learning experience based on your expertise.
Starting From
TBD
Duration
0 min
Get Life Time Access
₹0
₹499
100% off
Get Life Time Access
₹0
₹499
100% off