Machine Learning, Data Science & AI Engineering with Python
What you'll learn
- Build generative AI systems with OpenAI, RAG, and LLM Agents
- Build artificial neural networks with Tensorflow and Keras
- Implement machine learning at massive scale with Apache Spark's MLLib
- Classify images, data, and sentiments using deep learning
- Make predictions using linear regression, polynomial regression, and multivariate regression
- Data Visualization with MatPlotLib and Seaborn
- Understand reinforcement learning - and how to build a Pac-Man bot
- Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
- Use train/test and K-Fold cross validation to choose and tune your models
- Build a movie recommender system using item-based and user-based collaborative filtering
- Clean your input data to remove outliers
- Design and evaluate A/B tests using T-Tests and P-Values
Requirements
- You'll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software.
- Some prior coding or scripting experience is required.
- At least high school level math skills will be required.
Description
Master Machine Learning & AI Engineering — From Data Analytics to Agentic AI Solutions
Launch your career in AI with a comprehensive, hands-on course that takes you from beginner to advanced. Learn Python, data science, classical machine learning, and the latest in AI engineering—including generative AI, transformers, and LLM agents / agentic AI.
Why This Course?
Learn by Doing
With over 145 lectures and 21+ hours of video content, this course is built around practical Python projects and real-world use cases—not just theory.
Built for the Real World
Learn how companies like Google, Amazon, and OpenAI use AI to drive innovation. Our curriculum is based on skills in demand from leading tech employers.
No Experience? No Problem
Start from scratch with beginner-friendly lessons in Python and statistics. By the end, you’ll be building intelligent systems with cutting-edge AI tools.
A Structured Path from Beginner to AI Engineer
1. Programming Foundations
Start with a crash course in Python, designed for beginners. You’ll learn the language fundamentals needed for data science and AI work.
2. Data Science and Statistics
Build a solid foundation in data analysis, visualization, descriptive and inferential statistics, and feature engineering—essential skills for working with real-world datasets.
3. Classical Machine Learning
Explore supervised and unsupervised learning, including linear regression, decision trees, SVMs, clustering, ensemble models, and reinforcement learning.
4. Deep Learning with TensorFlow and Keras
Understand neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs), using real code examples and exercises.
5. Advanced AI Engineering and Generative AI
Go beyond traditional ML to learn the latest AI tools and techniques:
Transformers and self-attention mechanisms
GPT, ChatGPT, and the OpenAI API
Fine-tuning foundation models
Advanced Retrieval-Augmented Generation (RAG)
LangChain and LLM agents
Designing and building multi-agent systems with the OpenAI Agents SDK
Real-world GenAI projects and deployment strategies
6. Big Data and Apache Spark
Learn how to scale machine learning to large datasets using Spark, and apply ML techniques on distributed computing clusters.
Designed for Career Growth
Whether you're a programmer looking to pivot into AI or a tech professional seeking to expand your skills, this course delivers a complete, industry-relevant education. Concepts are explained clearly, in plain English, with a focus on applying what you learn.
What Students Are Saying
"I started doing your course... and it was pivotal in helping me transition into a role where I now solve corporate problems using AI. Your course demystified how to succeed in corporate AI research, making you the most impressive instructor in ML I've encountered."
— Kanad Basu, PhD
Enroll Today and Build Your Future in AI
Join thousands of learners who have used this course to land jobs, lead projects, and build real AI applications. Stay ahead in one of the fastest-growing fields in tech.
Start your journey today—from Python beginner to AI engineer.
Who this course is for:
- Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course.
- Technologists curious about how deep learning really works
- Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you'll need some prior experience in coding or scripting to be successful.
- If you have no prior coding or scripting experience, you should NOT take this course - yet. Go take an introductory Python course first.
Instructors
Sundog Education's mission is to make highly valuable career skills in data engineering, data science, generative AI, AWS, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford.
As a senior manager at Amazon during its early years, Frank Kane led large technical teams, managed multi-year projects, and served as a "bar-raiser" - interviewing thousands and hiring hundreds across the company.
Frank holds 26 issued patents in machine learning and personalization. After 9 years at Amazon and IMDb, he founded Sundog Education and has since taught over 1.1 million people in AI, ML, AWS, system design, and tech leadership. Frank has been teaching full-time for over 10 years - but is always building projects on the side with the latest emerging technologies, to better explain them to you!
Our teaching style is to simplify complex concepts - once you cut through all the notation and jargon, most of AI and machine learning is pretty easy to understand. We make these advanced topics accessible to anyone with a modest technical background, always using plain English and examples to drive it home. We make learning easy, hands-on, and fun.
Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. As an Amazon “bar raiser,” he held veto authority over hiring decisions across the company, interviewed over 1,000 candidates, and hired and managed hundreds. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own company, Sundog Software, which has taught over one million students around the world about machine learning, data engineering, and managing engineers.
Due to our volume of students, I am unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.
Our mission is to make highly valuable skills in machine learning, big data, AI, and data science accessible at prices anyone in the world can afford. Our current online courses have reached over 500,000 students worldwide. Sundog Education CEO, Frank Kane, spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaching others about big data analysis.