Why learn Machine Learning
with EduMonk?
Build a complete machine-learning workflow: define the prediction target, prepare features, train models, tune performance and communicate whether a model is ready for use.
The online syllabus follows a deliberate rhythm: learn the underlying concept, apply it in guided practice, confirm it with a checkpoint, and connect it to a project decision. By the end, you will have more than lesson completion—you will have evidence you can discuss.
Start learning for ₹1,650 today.
For the Machine Learning Certificate of Specialisation, pay ₹1,650 now and the remaining ₹1,500 next month. The two payments together cover the complete ₹3,150 programme fee.
Build the skills
behind your career.
Technical knowledge is only one part of becoming career-ready. Your Machine Learning enrolment also includes a focused professional-development journey at no additional cost.
FREE
EduMonk Career Edge
60-Day Soft Skills & Career Readiness Program
Spend approximately 20 minutes every day developing the communication, confidence, workplace and career-readiness skills that complement your technical education.
What you'll learn in Machine Learning.
Every outcome uses an observable action—something you can build, evaluate, explain or improve.
Where Machine Learning is used
Use the programme workflow to frame, build and evaluate demand forecasting.
Use the programme workflow to frame, build and evaluate risk and fraud scoring.
Use the programme workflow to frame, build and evaluate customer segmentation.
Use the programme workflow to frame, build and evaluate quality and anomaly detection.
Machine Learning skills
you'll build.
The programme develops eight connected skills and gives each one a place in the syllabus, lab work or assessment.
Your 2-month Machine Learning
learning plan.
A sustainable sequence that gives you time to understand, practise and produce useful work.
Enter AI foundations
Complete Introduction to Machine Learning and Python for Machine Learning.
Build with data and ML
Complete Mathematics & Statistics for Machine Learning, Data Preparation & Exploratory Data Analysis and the Level 1 projects.
Apply modern AI
Work through Modules 5–8 and complete the applied AI projects.
Understand generative systems
Complete Model Optimisation and Ensemble Machine Learning.
Build AI applications
Practise Introduction to Neural Networks and Machine Learning Pipelines.
Integrate, evaluate & demonstrate
Complete the remaining Level 3 modules and deliver the final specialisation capstone.
Machine Learning syllabus:
15 modules, 30 hours.
This is the complete planned syllabus for the Machine Learning Certificate of Specialisation. The 15 focused modules combine concept learning, hands-on practice and completion checks across the two-month journey.
Build practical capability in introduction to machine learning.
01What is Machine Learning?Lesson
02Artificial Intelligence vs Machine Learning vs Deep LearningLesson
03How Machine Learning systems workLesson
04Machine Learning lifecycleLesson
05Features and labelsLesson
06Training dataLesson
07Validation dataLesson
08Test dataLesson
Time includes lesson study, guided practice, checkpoint preparation and project integration. Learners may spend longer when extending project work.
Hands-on Machine Learning
course projects.
Build 9 practical applications across the syllabus's progressive levels. The 3 capstones ask you to combine each level's skills, evaluate the result and explain the decisions behind it.
House Price Prediction
Build, test and document a practical house price prediction using the skills developed in Level 1.
Customer Purchase Prediction
Build, test and document a practical customer purchase prediction using the skills developed in Level 1.
Customer Churn Prediction System
Build, test and document a practical customer churn prediction system using the skills developed in Level 1.
Credit Risk Prediction
Build, test and document a practical credit risk prediction using the skills developed in Level 2.
Customer Segmentation Engine
Build, test and document a practical customer segmentation engine using the skills developed in Level 2.
Fraud Detection System
Build, test and document a practical fraud detection system using the skills developed in Level 2.
Employee Attrition Prediction System
Build, test and document a practical employee attrition prediction system using the skills developed in Level 3.
Sales Forecasting System
Build, test and document a practical sales forecasting system using the skills developed in Level 3.
Intelligent Financial Loan Risk & Approval Platform
Build, test and document a practical intelligent financial loan risk & approval platform using the skills developed in Level 3.
Machine Learning tools you'll work with
How the Machine Learning
course is assessed.
Your result reflects steady application across the programme—not one high-pressure exam.
Module checkpoints
15 focused checks confirm that core concepts and terminology are secure.
Hands-on labs
Every module includes a guided lab tied directly to the syllabus.
Level projects
Complete 6 focused Machine Learning builds across the three levels.
Capstone projects
Plan, build, test and explain 3 progressively more complete solutions.
Certificate eligibility
Complete all required modules, submit the assignments and capstone, and achieve at least 60% overall.
Who should take this
Machine Learning course?
College students
Build practical Machine Learning evidence alongside your academic work.
Working professionals
Use Machine Learning to strengthen your current role or move towards artificial intelligence work.
Builders & analysts
Turn concepts into a guided project, capstone and documented decisions.
Career switchers
Follow a clear starting path with no assumption of professional experience.
Machine Learning course prerequisites
- Basic Python recommended
- Comfort with averages and percentages
- No previous machine-learning project required
- A willingness to practise and complete the capstone
Machine Learning career paths
and applications.
This programme does not promise a job. It helps you build relevant capability and evidence for conversations around roles such as:
Machine Learning guides,
roadmaps and comparisons.
Use these editorial resources to understand where Machine Learning fits, what a sensible learning path looks like and how to turn the subject into project evidence.
RoadmapArtificial Intelligence · Roadmap · 12 min readMachine Learning roadmapFollow a practical machine-learning roadmap through Python, data preparation, modelling, evaluation, projects and responsible deployment thinking.
Read the guide ↗
ComparisonArtificial Intelligence · Comparison · 10 min readDeep Learning vs Machine LearningCompare deep learning and machine learning by data needs, model complexity, skills, compute, projects and the right learning order for beginners.
Read the guide ↗Project guideArtificial Intelligence · Project guide · 11 min readMachine learning project guideBuild a credible machine-learning project through target definition, clean data splits, baselines, evaluation, error analysis and reproducible documentation.
Read the guide ↗Salary guideArtificial Intelligence · Salary guide · 10 min readMachine Learning Engineer Salary in IndiaUnderstand machine learning engineer salary in India through a dated market snapshot, role scope, pay drivers, portfolio evidence and a practical learning roadmap—without treating an average as a promise.
Read the guide ↗Your Machine Learning
Certificate & LOR.
Learners who successfully meet all programme completion requirements receive an EduMonk Certificate of Specialisation and a programme-specific Letter of Recommendation. Both documents are issued as soft copies, and hard copies are dispatched by post to the learner address on record.
Machine Learning Certificate of Specialisation
Machine Learning Letter of Recommendation
About these samplesFinal documents are personalised with the completed learner's name, programme record, dates and identifiers. Sample names and details are illustrative. Please keep the postal address in your learner record accurate for hard-copy dispatch.
Machine Learning course FAQs.
Is this specialisation beginner friendly?+
Machine Learning is marked intermediate. The syllabus begins with foundations and states any useful prior knowledge clearly. Professional experience is not required.
Is this a real 30-hour syllabus?+
Yes. The programme contains 15 focused modules with concept learning, hands-on practice and knowledge checks, planned across 30 learning hours in total.
What will I build?+
You will complete 9 projects across three levels, including 3 capstones. The sequence begins with House Price Prediction and culminates in the Intelligent Financial Loan Risk & Approval Platform.
How are learners assessed?+
Completion combines module checkpoints, hands-on labs, a guided project and the final capstone. A minimum overall score of 60% is required for certificate eligibility.
What support is included?+
Your enrolment includes the complete sequenced learning experience, downloadable resources, project guidance and learner support through the connected external learner portal.
Is EduMonk Career Edge included?+
Yes. This Certificate of Specialisation includes complimentary access to EduMonk Career Edge, a 60-day Soft Skills & Career Readiness Program with one focused lesson of approximately 20 minutes each day. Career Edge adds ₹0 to your ₹3,150 programme fee.
How do payment and programme access work?+
The Enrol Now button opens this specialisation’s secure Razorpay Payment Page. EduMonk does not collect card, UPI or bank credentials. After the payment is confirmed, access to this specialisation and EduMonk Career Edge is prepared manually and sent to your registered email within 4 hours.
What certificate will I receive?+
After meeting the completion requirements, you will earn a verifiable EduMonk Certificate of Specialisation in Machine Learning.
Which completion documents are issued?+
Learners who successfully meet the Machine Learning completion requirements receive a soft-copy Certificate of Specialisation and programme-specific Letter of Recommendation. Hard copies of both documents are also dispatched by post to the learner address on record.
How long can I access the programme?+
The structured learning journey lasts 2 Months. Access details, completion records and earned credentials are managed through the connected external learner portal.
