Machine Learning Fundamentals
Your complete introduction to machine learning. Understand the ML workflow, build and evaluate models with scikit-learn, and master the techniques behind every algorithm category.
What You'll Learn
Understand supervised, unsupervised, and reinforcement learning
Follow the complete ML workflow: data → features → model → evaluate → deploy
Build regression and classification models with scikit-learn
Evaluate models correctly using cross-validation and the right metrics
Apply feature engineering and selection to improve model performance
Tune hyperparameters with GridSearchCV and RandomizedSearchCV
Curriculum Breakdown
Learning Format
Video Lessons
High-quality recorded lessons you can watch at your own pace.
Hands-on Projects
Real-world projects that reinforce every concept you learn.
Certificate
Earn a verifiable certificate upon successful completion.
Certification Details
Machine Learning Fundamentals Certificate
Issued by Tech101
Validate your core machine learning knowledge with this widely recognised professional certificate.
Certificate Requirements
- Shareable on LinkedIn
- PDF download
- Unique verification ID
- Graded assessment included
Completion Certificate
Awarded upon finishing all course content and submitting projects. Shows dedication and completion.
Graded Certificate
Earned by passing the final assessment with 70%+ score. Demonstrates verified skill proficiency.
Your Instructor
Sarah Johnson
Data Scientist & ML Engineer
Sarah has 10 years of experience in data science and machine learning, previously at Google AI and DeepMind.
Requirements & Prerequisites
Technical Requirements
- Python, Pandas, and NumPy (take the earlier courses in this track)
- Basic statistics and probability knowledge
Who This Course Is For
- Data Science students ready to build their first ML models
- Software developers making the transition to ML
- Data Science & AI track students
Student Reviews
Frequently Asked Questions
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