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Learning paths
Foundational knowledge for a thriving AI and data science career
Whether you are an absolute beginner or a seasoned data scientist, follow one linear roadmap: take the courses in sequence, work through the notebooks, complete the assignments, solve industry-grade projects and build your profile.
Stage 01 of 08
Programming for AI/ML
Python, NumPy, pandas and SQL from the very first line, plus the big picture of how data science work fits together.
9 courses31 h of video2 free to start
- 01Foundations of Data Science (AI/ML): The Big Picture33 lessons · 2 h 22 min4.8Free
- 02Core Python Programming (Beginner)73 lessons · 5 h 36 minFree
- 03Numpy for Data Science46 lessons · 3 h 3 min4.9
- 04Pandas for Data Science115 lessons · 6 h 27 min4.7
- 05SQL for Data Science - Level I (Beginner)28 lessons · 2 h 33 min
- 06SQL for Data Science - Level II26 lessons · 1 h 30 min
- 07SQL for Data Science - Level III13 lessons · 1 h 14 min
- 08SQL for Data Science - Window Functions9 lessons · 1 h 6 min
- See all 9 courses in Programming for AI/ML
Stage 02 of 08
Statistics and ML Algorithms
The linear algebra and statistics underneath, then regression, classification, trees, ensembles and how to explain a model.
11 courses45 h of videoCertificates included
- 01Linear Algebra for Machine Learning20 lessons · 1 h 49 min
- 02Statistics for Data Science29 lessons · 2 h 49 min
- 03Data Pre-processing and EDA99 lessons · 7 h 3 min
- 04Linear Regression and Regularisation56 lessons · 7 h 28 min
- 05Classification: Logistic Regression36 lessons · 4 h 33 min
- 06Imbalanced Classification26 lessons · 2 h 47 min
- 07Supervised ML Algorithms63 lessons · 8 h 41 min
- 08Ensemble Learning28 lessons · 2 h 52 min
- See all 11 courses in Statistics and ML Algorithms
Stage 03 of 08
MLOps
Ship what you build: Docker, deployment on AWS, PySpark for big data and experiment tracking with MLflow.
12 courses18 h of videoCertificates included
- 01Docker for Data Science23 lessons · 1 h 57 min
- 02ML Deployment in AWS EC221 lessons · 1 h 59 min
- 03Deploy in AWS Lambda13 lessons · 1 h 4 min
- 04Deploy in AWS Sagemaker32 lessons · 2 h 45 min
- 05PySpark for Data Science - I: Fundamentals25 lessons · 2 h 3 min
- 06Automating AWS with Boto32 lessons · 1 h 9 min
- 07Automating AWS with Boto3 Part 2: Deploying PyTorch Models7 lessons · 1 h 23 min
- 08PySpark for Data Science - II: Statistics for Big Data23 lessons · 1 h 20 min
- See all 12 courses in MLOps
Stage 04 of 08
Deep Learning
Neural networks from the foundations to PyTorch, with computer vision and NLP projects.
6 courses6 h of videoCertificates included
- 01Foundations of Deep Learning in Python20 lessons · 1 h 6 min
- 02Foundation of Deep Learning - Part 231 lessons · 1 h 4 min
- 03Applied Deep Learning with PyTorch44 lessons · 1 h 31 min
- 04Detecting Defects in Steel Sheets with Computer Vision26 lessons · 1 h 26 min
- 05Project: Text Generation using Language Models with LSTM17 lessons · 31 min
- 06Project: Classifying Sentiment of Reviews using BERT (NLP)20 lessons · 25 min
Stage 05 of 08
Agentic AI
LangChain and LangGraph, retrieval augmented generation, agents and the Model Context Protocol.
10 courses16 h of videoCertificates included
- 01Mastering Langchain: Part 140 lessons · 3 h 40 min
- 02LangGraph 1019 lessons · 47 min
- 03LangGraph 20113 lessons · 1 h 40 min
- 04Retrieval Augmented Generation (RAG) Techniques17 lessons · 3 h 6 min
- 05Productionizing RAG System29 lessons · 1 h 36 min
- 06Building Agentic RAG19 lessons · 44 min
- 07Building a Complete Agentic AI App - Advanced9 lessons · 1 h 13 min
- 08Model Context Protocol (MCP)7 lessons · 1 h 37 min
- See all 10 courses in Agentic AI
Stage 06 of 08
Time Series Forecasting
From time series basics to ARIMA, vector autoregression and feature engineering for forecasting projects.
9 courses19 h of videoCertificates included
- 01Introduction to Time Series Analysis32 lessons · 3 h 33 min
- 02Time Series Analysis - I (Beginners)3 lessons · 1 h 34 min
- 03Time Series Analysis - II (Intermediate)3 lessons · 2 h 18 min
- 04Time Series Forecasting Part 1 - Statistical Models16 lessons · 1 h 30 min
- 05Time Series Forecasting Part 2 - ARIMA Modeling and Tests17 lessons · 1 h 48 min
- 06Time Series Forecasting Part 3 - Vector Auto Regression Methods28 lessons · 2 h 44 min
- 07Time Series Analysis - III: Singular Spectrum Analysis (SSA)20 lessons · 1 h 23 min
- 08Feature Engineering for Time Series Projects - I19 lessons · 1 h 28 min
- See all 9 courses in Time Series Forecasting
Stage 07 of 08
Industry DS Projects
Fifteen portfolio projects on real business problems: lifetime value, fraud, forecasting, marketing mix, uplift, pricing and survival analysis.
15 courses37 h of videoPortfolio ready
- 01Portfolio Project: Estimating Customer Lifetime Value for Business CLTV32 lessons · 3 h 30 min
- 02Portfolio Project: Microsoft Malware Detection Project41 lessons · 4 h 47 min4.7
- 03Portfolio Project: Credit Card Fraud Detection for Vesta51 lessons · 5 h 5 min4.8
- 04Portfolio Project: Restaurant Visitor Forecasting for Recruit57 lessons · 4 h 45 min4.8
- 05Portfolio Project: Optimizing marketing spend using Market Mix Modeling (MMM)36 lessons · 4 h 19 min
- 06Portfolio Project: Predict Rating given Amazon Product Reviews using NLP27 lessons · 1 h 48 min
- 07Uplift modeling: Estimating incremental impact of Marketing Campaigns12 lessons · 1 h 22 min
- 08Uplift Modeling Part 2: Modeling Strategies19 lessons · 1 h 21 min
- See all 15 courses in Industry DS Projects
Stage 08 of 08
Special Topics
Optimization, NLP with spaCy, R for data science and the Linux command line.
13 courses29 h of videoCertificates included
- 01Introduction to Optimization: Linear Programming23 lessons · 1 h 22 min
- 02Project: Inventory Planning and Holding Cost Optimization6 lessons · 59 min
- 03Optimization Part 2: Integer Programming4 lessons · 27 min
- 04Non Linear Optimization11 lessons · 1 h 23 min
- 05Spacy for NLP66 lessons · 4 h 24 min4.8
- 06Base R Programming80 lessons · 6 h 45 min4.6
- 07Dplyr for data wrangling14 lessons · 36 min4.7
- 08Wrangling data with Data.Table16 lessons · 49 min4.8
- See all 13 courses in Special Topics
Job titles are indicative and can vary with an organization’s internal designations.
Features comparison
A better way to learn AI and data science
How the full program compares with the usual places people learn.
| Feature | Udemy / MOOCs | YouTube | Coursera | Machine Learning Plus |
|---|---|---|---|---|
| Clearly explained | ||||
| Math behind algorithms | ||||
| Hands-on coding | ||||
| Reference material | ||||
| Supplementary courses | ||||
| Doubt support | ||||
| Completion certificate | ||||
| Live sessions access | ||||
| Industry-grade projects | ||||
| End-to-end DS roadmap | ||||
| 1:1 mentorship | ||||
| Mock interviews |
Everything you need for AI/ML prep.
From basic Python programming to deep learning and everything in between, we have got you covered.
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- Project & Coding Challenges
- Practice Exercises
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Alumni testimonials
Learners from 78+ countries
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4.92from 3,965 ratings · learners now at Google, Amazon, PayPal, Deloitte, Databricks and SAP
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FAQ
Frequently asked questions
Still unsure which course to start with? Write to us and we will help you choose.
Drop a queryNo. You can start even if you have no coding experience or background. We teach the Python programming needed for data science from scratch.
You can sign in and immediately access the code downloads, Jupyter notebooks, video lessons, courses and certificates of completion.
No. All courses and coding exercises can be completed in your browser, with pre-configured Jupyter notebooks that run in the cloud. If you prefer to set up your own machine, we provide install instructions as well.
Ask for a refund within 30 days of purchase, one refund per customer per product. The amount reaches you in 5 to 7 working days, depending on the payment method. Contact us if you have any trouble accessing a course.
No. Everything is laid out as one structured path that you take in sequence. That structure gives you direction and achievable goals, and when each concept is clearly explained, AI and data science become very doable.
You can meet and talk with data scientists in the weekend sessions, and ask for a phone call back by emailing us. For small technical questions, the course forum is the quickest place to get an answer.
Write to team@machinelearningplus.com or message us on WhatsApp at +91 88256 46700.