Project-based learning
Build real work you can show in interviews.
Course details
Machine Learning
Train models that learn from data and predict real outcomes.
Taught by Tejasree Desamsetty · Full Stack Developer
CertificateIncluded on completion
Lifetime access
Revisit lessons anytime after you enroll.
Mentor support
Learn with guidance from industry experts.
Career-ready skills
Practical modules aligned to real roles.
Overview
What this course covers
Learn how machines find patterns in data and turn them into predictions. From regression to ensemble models and neural networks, you will build, evaluate, and tune real models using Python and scikit-learn.
Outcome
Finish with practical skills and a portfolio-ready project in Machine Learning you can use for jobs, freelancing, or your next role.
Skills
What you'll learn
Supervised and unsupervised learning
Regression, classification & clustering
Feature engineering and model evaluation
Decision trees, random forests & boosting
Intro to neural networks
Deploying models to production
Audience
Who this course is for
Beginners
Starting Machine Learning from scratch and want a clear path.
Students & grads
Building a portfolio and interview-ready skills.
Working pros
Upskilling into ai roles with practical projects.
Before you start
Prerequisites
- Basic computer and internet skills
- Curiosity and consistency to practise weekly
- Open to learners of every background
Syllabus
Curriculum overview
8 modules · project-based lessons · certificate on completion
01Module 1: ML Foundations & Workflow
Hands-on lessons, examples, and a guided exercise covering ml foundations & workflow.
02Module 2: Data Preprocessing & Features
Hands-on lessons, examples, and a guided exercise covering data preprocessing & features.
03Module 3: Regression Models
Hands-on lessons, examples, and a guided exercise covering regression models.
04Module 4: Classification Models
Hands-on lessons, examples, and a guided exercise covering classification models.
05Module 5: Clustering & Dimensionality Reduction
Hands-on lessons, examples, and a guided exercise covering clustering & dimensionality reduction.
06Module 6: Ensemble Methods
Hands-on lessons, examples, and a guided exercise covering ensemble methods.
07Module 7: Neural Networks Intro
Hands-on lessons, examples, and a guided exercise covering neural networks intro.
08Module 8: Model Deployment Project
Hands-on lessons, examples, and a guided exercise covering model deployment project.
After the course
You'll walk away ready
By completing this course, you will have the practical skills and a portfolio project in Machine Learning to confidently move forward in your career.
- Job-ready ai fundamentals
- A completed capstone you can showcase
- Certificate of completion from Syncpedia
Faculty
Learn with our mentors
Guides practical QA workflows, automation foundations, and career-ready project reviews.
Mentors end-to-end builds, clean code habits, and shipping full-stack projects with confidence.
Supports career direction, interview readiness, and growth plans for every learner.
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