Online RESOURCES

Contents: Python basics, API programming
By: Andrew Ng, Stanford University

Link: https://www.deeplearning.ai/short-courses/ai-python-for-beginners/

Contents: Introduction to AI, methods, applications, ethics
By: University of Helsinki
Link: https://www.elementsofai.com/

Contents: Python basics, data structures, web scraping, databases
By: University of Michigan
Link: https://www.coursera.org/specializations/python

Contents: Data analysis with Python, NumPy, Pandas

By: IBM

Link: https://www.coursera.org/learn/data-analysis-with-python

Contents: Python basics, strings, lists, sorting, dicts, files, regex

By: Google

Link: https://developers.google.com/edu/python

Contents: Introduction to NumPy, arrays, operations

By: W3Schools

Link: https://www.w3schools.com/python/numpy/

Contents: Introduction to Pandas, dataframes, series, operations

By: W3Schools

Link: https://www.w3schools.com/python/pandas/

Contents: Python programming, computational thinking

By: MIT OpenCourseWare

Link: https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/Add a description about this item

Contents: Image processing, feature detection, image matching

By: University at Buffalo, Coursera

Link (Audit): https://www.coursera.org/learn/computer-vision-basic

Contents: Python basics, data structures, file I/O

By: Eric Matthes

Link (Sample chapters free): https://www.nostarch.com/pythoncrashcourse2

Contents: Python programming, algorithms, debugging
By: Allen B. Downey
Link: https://greenteapress.com/wp/think-python-2e

Contents: Practical Python: automation, web scraping, working with files

By: Al Sweigart

Link: https://automatetheboringstuff.com/#tocAdd a description about this item

Contents: LLM basics with most intuitive explanations
By: Jay et al.
Link: https://www.amazon.com/Hands-Large-Language-Models-Understanding/dp/109815096

Contents: Generative AI intro

By: Microsoft

Link: https://microsoft.github.io/generative-ai-for-beginners/#/

Contents: Agents intro

By: Hugging Face

Link: https://huggingface.co/agents-course 

Contents: ML with Scikit-learn: classification, regression, clustering
By: IBM
Link: https://www.coursera.org/learn/machine-learning-with-python

Contents: Text processing, classification, tagging, parsing
By: NLTK
Link: https://www.nltk.org/book/

Contents: ML basics with Scikit-learn: classification, regression, clustering
By: Andreas C. Müller, Sarah Guido
Link (Free via some libraries or promotions): https://www.oreilly.com/library/view/introduction-to-machine/9781449369880/Add a description about this item

Contents: Supervised and unsupervised learning, best practices
By: Andrew Ng, Stanford University
Link: https://www.deeplearning.ai/courses/machine-learning-specialization/

Contents: Deep Learning
By: Andrew Ng, Stanford University
Link: https://www.deeplearning.ai/courses/deep-learning-specialization/

Contents: Deep learning concepts, neural networks
By: François Chollet
Link (Free chapter previews): https://www.manning.com/books/deep-learning-with-python

Contents: Deep learning fundamentals with PyTorch
By: Udacity, Facebook AI
Link: https://www.udacity.com/course/deep-learning-pytorch--ud188

Contents: Neural network fundamentals, backpropagation, deep learning

By: Michael Nielsen

Link: http://neuralnetworksanddeeplearning.com/Add a description about this item

Contents: Lecture notes, assignments on ML topics
By: MIT OpenCourseWare
Link: https://ocw.mit.edu/courses/6-036-introduction-to-machine-learning-fall-2020/

Contents: Lecture notes, assignments on AI topics

By: MIT OpenCourseWare

Link: https://ocw.mit.edu/courses/6-034-artificial-intelligence-fall-2010

Contents: Image processing, feature detection, recognition

By: Richard Szeliski

Link (Draft version free): https://ocw.mit.edu/courses/6-034-artificial-intelligence-fall-2010/