Others / Resources / Interview / Learning / Courses

• Intro to graph neural networks (ML Tech Talks)
• Machine Learning Course for Beginners
• https://github.com/josephmisiti/awesome-machine-learning
• https://www.freecodecamp.org/news/best-machine-learning-courses
• AI Engineer Roadmap – How to Learn AI in 2025 - YouTube

LLM / GenAI

• AI Canon | Andreessen Horowitz
• LLM - dbdemos Build your Chat Bot with Dolly - Databricks demos
• CS 886: Recent Advances on Foundation Models
• LLM Bootcamp - Spring 2023 - The Full Stack
• GitHub - microsoft/generative-ai-for-beginners: 18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/ ⭐ 112k
• AI Skills Navigator
  • Career Essentials in Generative AI by Microsoft and LinkedIn Learning Path | LinkedIn Learning, formerly Lynda.com
  • Microsoft Launches New AI Skills Training and Resources as part of Skill for Jobs Initiative
  • Ignite Edition Challenge: Microsoft Learn Challenge | Microsoft Learn
• Hands-On Large Language Models
• Jay Alammar – Visualizing machine learning one concept at a time.
• GitHub - microsoft/ai-agents-for-beginners: 10 Lessons to Get Started Building AI Agents ⭐ 67k
• The Generative AI Learning Roadmap
• Research papers for software engineers to transition to AI Engineering. - YouTube
• Generative AI Bootcamp – Complete 65-Hour Course - YouTube
• GitHub - mlabonne/llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. ⭐ 80k
• Reinforcement Learning Guide | Unsloth Documentation
• GitHub - afshinea/stanford-cme-295-transformers-large-language-models: VIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models ⭐ 4.5k
• GitHub - patchy631/ai-engineering-hub: In-depth tutorials on LLMs, RAGs and real-world AI agent applications. ⭐ 36k
• GitHub - rasbt/LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step ⭐ 97k
• I taught myself GenAI from scratch, and it made me the go-to AI expert in my org at Microsoft, and these are my favourite resources to set you up on the same path | Shivani Virdi
• Top 7
  • GitHub - HandsOnLLM/Hands-On-Large-Language-Models: Official code repo for the O'Reilly Book - "Hands-On Large Language Models" ⭐ 27k
  • GitHub - punkpeye/awesome-mcp-servers: A collection of MCP servers. ⭐ 89k
  • GitHub - NirDiamant/GenAI_Agents: This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive AI systems. ⭐ 22k
  • GitHub - GokuMohandas/Made-With-ML: Learn how to design, develop, deploy and iterate on production-grade ML applications. ⭐ 48k
  • GitHub - dair-ai/Prompt-Engineering-Guide: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering ⭐ 76k
  • GitHub - microsoft/ai-agents-for-beginners: 11 Lessons to Get Started Building AI Agents ⭐ 67k
  • GitHub - punkpeye/awesome-mcp-clients: A collection of MCP clients. ⭐ 6.5k
• Antropic - X
  • Claude with the Anthropic API
  • Claude with Amazon Bedrock
  • Claude with Google Cloud's Vertex AI
  • Introduction to Model Context Protocol
  • Model Context Protocol: Advanced Topics
  • Claude Code in Action
• Ed Donner | AI startup co-founder and leader; Gen AI and LLM instructor | Udemy
• Attention in Transformers: Concepts and Code in PyTorch - DeepLearning.AI

1 Deep Dive into LLMs like ChatGPT (by Andrej Karpathy) ↳ Explains full LLM training stack, the foundation agent builders need 🔗 https://lnkd.in/eiJeGN3n

2 AI Agents for Beginners (by Microsoft) ↳ Microsoft's agent curriculum in one video 🔗 https://lnkd.in/ep4Rgxjp

3 LangGraph Complete Course for Beginners (by freeCodeCamp) ↳ Builds agents from scratch 🔗 https://lnkd.in/emzaYing

4 GenAI Essentials Full Course (by freeCodeCamp) ↳ Covers the entire GenAI lifecycle 🔗 https://lnkd.in/eMqV9XRx

5 Build n8n AI Agents (by Nate Herk) ↳ Teaches you no-code agent builds & multi-agent architectures 🔗 https://lnkd.in/etGUZcwn

6 Complete Agentic AI Course (by Krish Naik) ↳ Teaches LangChain, LangGraph, RAG, guardrails & evals 🔗 https://lnkd.in/eRx6Kjkk

7 Agentic AI Crash Course using LangChain (by CampusX) ↳ Theory of generative & agentic AI 🔗 https://lnkd.in/e9FptHJY

8 AI Agents for Beginners (by KodeKloud) ↳ Builds agent personalities from scratch 🔗 https://lnkd.in/eb5Rvg-y

9 Generative AI Full Course (by freeCodeCamp) ↳ GenAI & agent courses in one playlist 🔗 https://lnkd.in/eJuJky4h

10 Master Agentic AI ↳ Condenses current agent concepts & tooling into 2 hours 🔗 https://lnkd.in/eq2KQ8fw

LLM Engineering

1. LangGraph Complete Course for Beginners – Complex AI Agents with Python - YouTube
2. Agentic AI With Langgraph And MCP Crash Course-Part 1 - YouTube
3. LLM Engineering: Master AI, Large Language Models & Agents | Udemy
4. The Complete Agentic AI Engineering Course (2025) | Udemy
5. CS146S Course: The Modern Software Developer | Stanford University Bulletin

AI (Artificial Intelligence) + ML (Machine Learning)

• https://www.freecodecamp.org/learn/machine-learning-with-python
• OpenCV - https://www.youtube.com/watch?v=P4Z8_qe2Cu0
• D2l.ai + coursera + fast.ai
• Kaggle
• AI - Model serving framework
• https://www.kaggle.com/learn
• Data modelling
• FinGPT: Open-Source Financial Large Language Models
• Learn Machine Learning in 3 Months (PyTorch Curriculum) - YouTube
• AI Jesus Made Me a Believer - YouTube
• Master Coding for Data Science - StrataScratch
• Harvard CS50's Introduction to Artificial Intelligence with Python - Free University Course
• Mathematics (probability, statistics, calculus)
• Machine Learning & Neural Networks without Libraries - No Black Box Course - YouTube
• udlbook
• Learn Machine Learning in 2024
• 5 Free AI Courses With Certifications In 2024
• A Roadmap for Your Machine Learning Career - MachineLearningMastery.com
• AWS Certified AI Practitioner (AIF-C01) – Full Course to PASS the Certification Exam - YouTube
• Generative AI for Everyone
• GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all ⭐ 87k 72.5K stars
• GitHub - GokuMohandas/Made-With-ML: Learn how to design, develop, deploy and iterate on production-grade ML applications. ⭐ 48k

DS (Data Science) + DA (Data Analytics) + DE (Data Engineering)

• Tool - dbt, fivetran, Informatica
• GitHub - DataEngineer-io/data-engineer-handbook: This is a repo with links to everything you'd ever want to learn about data engineering ⭐ 42k
• IOT & Predictive maintenance
• Data Analysis with Python Certification | freeCodeCamp.org
• DS - Pandas and Numpy + Scipy + scikit-learn
• Data Analytics Certification (powerbi / tableau)
• Credit Risk Modeling (Data Science)
• https://www.analyticsvidhya.com/blog/2019/12/30-challenging-open-source-data-science-projects-2020
• scipy documentation
• Python for DS - Freecodecamp certification
• https://www.startdataengineering.com/post/data-engineering-project-to-impress-hiring-managers
• Data Engineering Study Guide
• Learn Pandas & Python for Data Analysis - Full Course
• SQL Interview Prep With Zach Wilson - YouTube
• Google Advanced Data Analytics Professional Certificate | Coursera
• GitHub - alfarias/awesome-kaggle-kernels: Compilation of good Kaggle Kernels. ⭐ 62

Courses ML & AI

• https://www.freecodecamp.org/news/machine-learning-for-everybody
• https://github.com/GoogleCloudPlatform/training-data-analyst
• https://www.datacamp.com/courses/machine-learning-with-tree-based-models-in-python
• CS 498 Applied Machine Learning
• STAT 420 Methods of Applied Statistics
• STAT 571 Multivariate Analysis
• CS 410 Text Information Systems
• https://github.com/GokuMohandas/practicalAI
• STAT 542 Practical Statistical Learning Causal Inference / Econometrics
• JASON@MLMastery 14 day course email
• Adrian@pysearchimage 17 day ml course email
• https://www.kaggle.com/c/titanic
• https://github.com/Avik-Jain/100-Days-Of-ML-Code
• https://www.elementsofai.com
• Learning from Data Course by Prof Yaser Abu-Mostafa
• FREE - Google's ML Crash Course
• FREE - course.fast.ai
• Free Computation Linear Algebra - https://www.fast.ai/2017/07/17/num-lin-alg
• Neural Networks and Deep Learning by Andrew Ng
• Stanford's ML Course by Andrew Ng
• The school of AI - Move37
• The school of AI - Decentralized Applications
• https://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=99107737
• https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010
• https://madewithml.com
• https://www.coursera.org/specializations/practical-data-science
• https://www.edx.org/course/fundamentals-of-tinyml
• https://www.univ.ai
• Interpretable Machine Learning
• Paid - Complete Machine Learning & Data Science Program
• Roadmap - Sreedath Panat on LinkedIn: An 8-month roadmap to ML (Sorry there are no shortcuts) Stepping into ML… | 19 comments

Courses - Data

• https://stories.thedataproject.net
• https://www.alphaa.ai/saurabh-moody (Certification Free)
• Python for data science
• Data Warehousing & Business Intelligence
• Bipedal robot walker openai gym move37 course
• https://www.kaggle.com/learn/data-visualization-from-non-coder-to-coder
• WorldQuant University Scientific Computing and Python for Data Science
• https://www.coursera.org/specializations/data-mining
• https://www.edx.org/course/data-science-wrangling-2
• https://lagunita.stanford.edu/courses/course-v1:ComputerScience+MMDS+SelfPaced/about
• https://www.coursera.org/specializations/big-data
• https://onlinecourses.nptel.ac.in/noc19_cs33/course
• https://in.udacity.com/course/data-science-interview-prep--ud944
• PGDAST - Post Graduate Diploma in Applied Statistics - IGNOU
• Applied Data Science in Python
• https://in.udacity.com/course/data-wrangling-with-mongodb--ud032
• https://www.coursera.org/specializations/data-science
• scikit-learn
• freecodecamp.org data visualization certification
• Training data analyst google github https://github.com/GoogleCloudPlatform/training-data-analyst
• Data science for startup - https://bgweber.github.io
• Readings in applied data science - https://github.com/hadley/stats337
• Fundamentals of data vizualization - https://serialmentor.com/dataviz
• Spark - https://cognitiveclass.ai/learn/spark
  • Spark, storm, flink
  • Athena / Presto / Hive
• HDFS Architecture - https://hadoop.apache.org/docs/r3.0.0/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html
• Computer Vision - https://in.udacity.com/course/introduction-to-computer-vision--ud810
• NPTEL - Data Mining - https://onlinecourses.nptel.ac.in/noc19_cs15
• NPTEL - Big Data Computing - https://onlinecourses.nptel.ac.in/noc19_cs33/course
• https://www.analyticsvidhya.com/blog/2019/12/30-challenging-open-source-data-science-projects-2020
• Dagster POC
• https://realpython.com/pandas-groupby
• https://realpython.com/build-recommendation-engine-collaborative-filtering
• https://realpython.com/python-statistics
• https://www.sketchingbigdata.org
• https://realpython.com/numpy-array-programming
• https://github.com/guipsamora/pandas_exercises
• https://www.kaggle.com/learn/overview
• [GOOD] https://www.coursera.org/specializations/big-data-engineering
• https://github.com/adilkhash/Data-Engineering-HowTo
• https://in.udacity.com/course/intro-to-data-science--ud359
• https://in.udacity.com/course/intro-to-data-analysis--ud170-india
• Google Cloud Coursera free specialization
• https://www.udemy.com/applied-deep-learningtm-the-complete-self-driving-car-course
• Python for Data Science by Indian Institute of Technology Madras via Swayam
• Python and Statistics for Financial Analysis by The Hong Kong University of Science and Technology via Coursera
• https://www.youtube.com/365datascience
• https://www.coursera.org/professional-certificates/gcp-data-engineering
• https://www.coursera.org/specializations/data-science-python
• https://www.freecodecamp.org/news/algorithmic-trading-using-python-course
• https://www.freecodecamp.org/news/hands-on-data-science-course

Others

• Statistics and EDA
• Data Visualization
• Descriptive Statistics
• central tendency and variability
• Inferential Statistics
• probability, central limit theorem and more to draw inferences
• Exploratory Data Analysis
• Hypothesis Testing
• Case Study - Uber supply demand gap

Introduction to ML 1

• Linear Regression
• predict continuous data values
• Supervised Classification
• KNN, Naives Bayes and Logistic Regression
• Clustering
• K-Means and Hierarchical Clustering
• Case Study - Telecom Churn

Introduction to ML 2

• Time Series
• Decision Trees
• Support Vector Machines
• Neural Networks
• Master Feed-forward, Recurrent and Gaussian Neural Networks.
• Association Rule Mining
• BIG DATA ANALYTICS
• INTRODUCTION TO BIG DATA AND HADOOP
• Understand the basic concepts of Big Data and Hadoop as processing platforms for Big Data
• MANAGING BIG DATA
• Learn and use Hadoop ecosystem tools like Sqoop & Hive for data ingestion, extraction and management.
• INTRODUCTION TO SPARK
• Understand and use Spark, a fast Big Data processing platform
• BIG DATA ANALYSIS
• Learn how to analyze Big Data using SparkR, SparkSQL
• Domain Electives
• BFS
• Learn Customer analytics and Risk Analytics within BFS (Banking and Financial Services)
• E-commerce
• Customer marketing analytics and recommendation engines
• Health care

Model resources

• https://paperswithcode.com/
• https://paperswithcode.com/sota
• https://github.com/tensorflow/models ⭐ 78k
• https://github.com/academic/awesome-datascience
• https://mlcourse.ai/roadmap
• https://whimsical.com/machine-learning-roadmap-2020-CA7f3ykvXpnJ9Az32vYXva
• https://i.am.ai/roadmap
• https://github.com/MrMimic/data-scientist-roadmap

• https://github.com/tirthajyoti/Data-science-best-resources/blob/master/README
• https://github.com/FavioVazquez/ds-cheatsheets
• https://github.com/jonathan-bower/DataScienceResources
• https://towardsdatascience.com/5-professional-projects-every-data-scientist-should-know-e89bf4e7e8e1

1. Customer Segmentation
2. Text Classification
3. Sentiment Analysis
4. Time Series Forecasting
5. Recommendation Systems

Courses

• https://www.freecodecamp.org/news/statistics-for-data-science
• https://www.freecodecamp.org/news/how-to-analyze-data-with-python-pandas
• https://www.coursera.org/learn/machine-learning
• Free - (7 Weeks each)
• http://course.fast.ai
• http://course.fast.ai/part2.html
• https://github.com/josephmisiti/awesome-machine-learning/blob/master/books

Machine Learning

• https://www.toptal.com/machine-learning/machine-learning-theory-an-introductory-primer
• https://www.toptal.com/machine-learning/interview-questions
• https://semanti.ca/blog/?the-most-important-machine-learning-algorithms
• https://www.uruit.com/machine-learning-guide/
• How to approach ml problems - https://www.toptal.com/machine-learning/machine-learning-problems
• https://github.com/trekhleb/homemade-machine-learning
• Convoluational neural network - https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480
• https://ahmedbesbes.com/end-to-end-ml.html
• https://developers.google.com/machine-learning/crash-course/
• https://madewithml.com
• https://madewithml.com/topics
• https://www.freecodecamp.org/news/a-no-code-intro-to-the-9-most-important-machine-learning-algorithms-today/
• https://aws.amazon.com/blogs/machine-learning/amazons-own-machine-learning-university-now-available-to-all-developers
• https://www.freecodecamp.org/news/free-machine-learning-course-10-hourse

Cheatsheet

• https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks
• https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-supervised-learning
• https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-unsupervised-learning
• Cheat Sheets for Machine Learning Interview Topics | by Aqeel Anwar | Medium
  • www.cheatsheets.aqeel-anwar.com

NewsLetter & Blogs

• https://blog.udacity.com/2018/03/5-must-read-ai-newsletters.html
• https://medium.com/@ageitgey
• https://distill.pub
• https://i.am.ai

Examples

https://towardsdatascience.com/how-to-build-a-real-time-fraud-detection-pipeline-using-faust-and-mlflow-24e787dd51fa

Resources

• https://www.toptal.com/machine-learning/tensorflow-machine-learning-tutorial
• https://www.inference.vc/untitled

Questions

• http://onlinetutorials.today/data-science/data-science-interview-questions-and-answers
• https://medium.com/@leventov/design-of-a-cost-efficient-time-series-store-for-big-data-88c5dc41af8e
• https://www.fast.ai/2020/01/07/data-questionnaire
• https://www.conordewey.com/blog/the-big-list-of-data-science-interview-resources
• https://towardsdatascience.com/the-uber-data-scientist-interview-7ba9ca95f4e3

Links

• Understand ANY Machine Learning Model - YouTube
• 9.5 Shapley Values | Interpretable Machine Learning
• It's All About AI • Martin Förtsch, Thomas Endres & Jonas Mayer • YOW! 2022 - YouTube
• The State of Competitive Machine Learning | ML Contests
• Deep-ML
• Big Data Engineer Mock Interview | AWS | Kafka Streaming | SQL | PySpark Optimization #interview - YouTube