Educational resources for self-learners
Simulation and modeling of natural processes
Offered by University of Geneva. This course gives you an introduction to modeling methods and simulation tools for a wide range of natural phenomena. You'll cover Python programming, dynamical systems, numerical integration, cellular automata, and agent-based models, including a section on optimization problems. This is perfect for applying computational methods to understand and optimize complex systems, aligning with your interests in programming, mathematics, and startups. The course includes full-length video lectures with subtitles and practical assignments.
Cristina Gurguta - Prompt Engineering Mentor
Cristina Gurguta is an AI & ML Manager for Strategic Portfolios at HOLCIM and a Prompt Engineering mentor on MentorCruise. She has over 15 years of global experience in AI strategy, MLOps, and team leadership. She speaks English and Romanian, and offers expertise in MLops, Data Science, Machine Learning, and Python.
Chouaieb Nemri - Prompt Engineering Mentor
Chouaieb Nemri is a Generative AI BlackBelt Specialist at Google with over 10 years of experience in Data, Cloud, and Artificial Intelligence. He helps executives and leaders accelerate their cloud-based AI/ML and Generative AI initiatives. He offers expertise in Aws, Python, Machine Learning, and Data Science.
Leoson Hoay - Prompt Engineering Tutor
Leoson Hoay is a Consultant (Data Science and AI) at Diffusion Venture Studio. He speaks English, Chinese, and Japanese, and is an Interdisciplinary Data Scientist and VC Consultant. He is passionate about leveraging technology to solve problems and offers expertise in Data Science, LLM, AI, and Machine Learning.
Prompt Engineering for LLMs: The Art and Science of Building Large Language Model‑Based Applications
This book teaches how to communicate effectively with large language models by crafting prompts that harness their full potential, covering foundational concepts and advanced techniques such as few-shot learning, chain-of-thought prompting, and retrieval-augmented generation (RAG).
The only video you need to understand Gradient Descent!!
This YouTube Short visually explains gradient descent, showing how the algorithm moves along a slope to find a minimum. It is relevant to programming and AI by focusing on the core concept used in optimization algorithms.
Visually Explained
Visually Explained creates concise and intuitive animated videos on complex topics in mathematics and machine learning.
Mathematical Optimization for Real-World Decisions
An insightful podcast episode explaining mathematical optimization, its core concepts, and practical applications in programming, startups, and product design, featuring Jerry Yurchisin from Gurobi.
Infinite Codes
Infinite Codes creates short, animated explanations of complex tech and math concepts, making them accessible to a wide audience.
Data Professor
Data Professor creates educational content on data science, machine learning, and programming.
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