Are you ready to take a deeper dive into mastering the concepts and techniques involved in machine learning? This learning path shows how machine learning algorithms work and how to design them yourself. There's a lot to learn in this rapidly growing (and highly recuited-for) field, and these courses will give you an extremely solid skill set.
Explore the concepts and techniques behind designing machine learning algorithms
Learn how recommendation systems work and how to build them
Master how to design machine solutions for different applications
Machine Learning and AI Foundations: Decision Trees with Keith McCormick
Establish a strong foundation in ML by exploring the IBM SPSS Modeler and learning about CHAID and C&RT. This course is designed to help expand your data science skills.
1h 16m • COURSE
Deploying Scalable Machine Learning for Data Science with Dan Sullivan
Learn how to use design patterns for scalable architecture and tools such as services and containers to deploy machine learning at scale.
1h 43m • COURSE
Building a Recommendation System with Python Machine Learning & AI with Lillian Pierson, P.E.
Discover how to use Python to build programs that can make recommendations. This hands-on course explores different types of recommendation systems, and shows how to build each one.
1h 38m • COURSE
Machine Learning and AI Foundations: Clustering and Association with Keith McCormick
Learn how to use cluster analysis, association rules, and anomaly detection algorithms for unsupervised learning.
3h 22m • COURSE
Machine Learning & AI: Advanced Decision Trees with Keith McCormick
Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.
1h 16m • COURSE
Machine Learning and AI Foundations: Classification Modeling with Keith McCormick
Classification methods are among the most important in modern data science. Learn classification strategies and algorithms for machining learning and AI.
2h • COURSE
Machine Learning and AI Foundations: Value Estimations with Adam Geitgey
Discover how to solve value estimation problems with machine learning. Learn how to build a value estimation system that can estimate the value of a home.
1h 4m • COURSE
Machine Learning & AI Foundations: Linear Regression with Keith McCormick
Expand your data science skills by learning how to leverage the concepts of linear regression to solve real-world problems.
3h 57m • COURSE
Machine Learning and AI Foundations: Recommendations with Adam Geitgey
This project-based course shows programmers of all skill levels how to use machine learning to build programs that can make recommendations—like recommending new products to customers based on how they reviewed other products.
58m 7s • COURSE
You'll learn AI and machine learning skills with these experts.
Keith McCormick is an independent data miner, trainer, speaker, and author.
Keith is skilled at explaining complex methods to new users or decision makers at many levels of technical detail. He specializes in predictive models and segmentation analysis including classification trees, neural nets, general linear model, cluster analysis, and association rules.
Dan Sullivan, PhD, is an enterprise architect and big data expert.
Dan specializes in data architecture, analytics, data mining, statistics, data modeling, big data, and cloud computing. In addition, he holds a PhD in genetics, bioinformatics, and computational biology. Dan works regularly with Spark, Oracle, NoSQL, MongoDB, Redis, R, and Python. He has extensive writing experience in topics including cloud computing, big data, Hadoop, and security.
Lillian Pierson, P.E. is a leading expert in the field of big data and data science.
She equips working professionals and students with the data skills they need to stay competitive in today's data-driven economy.
Lillian has recently become a data science instructor for multiple courses on LinkedIn Learning. She's also the author of several highly-referenced technical books by the John Wiley & Sons, Inc. publishing company—including Data Science for Dummies (2017, 2015)—and has spent the last decade training and consulting for large technical organizations in the private sector, such as IBM, BMC, Dell, and Intel, as well as government organizations, from the US Navy down to the local government level.
As the Founder of Data-Mania LLC, Lillian offers online and face-to-face training courses, as well as workshops and other educational materials in the area of big data, data science, and data analytics.
Adam Geitgey is a developer who is captivated by how machine learning is changing software development.
His background is in building large-scale websites and helping startups in Silicon Valley take advantage of machine learning. He has a passion for putting theory into practice—taking cutting-edge developments in machine learning and sharing them with software developers of all skill levels.