Introduction to Python Programming
Learn the basics of Python programming in this introductory course. You will be guided step by step in the world's most popular beginning programming language.
Unlock the power of data and innovation with online courses designed for learners who want to build real-world technical skills. Whether you’re new to programming or looking to expand your analytics toolkit, these two courses will guide you through the fundamentals of Python and the core principles of machine learning. You’ll gain practical experience writing code, training models, and interpreting results using industry-standard tools. By the end, you’ll be equipped to apply machine learning techniques to solve problems, make data-driven decisions, and advance your career in the rapidly growing field of artificial intelligence.
Learn the basics of Python programming in this introductory course. You will be guided step by step in the world's most popular beginning programming language.
This course dives into Machine Learning and AI. Discussions will include a variety of machine learning techniques and their application to actual data.
Students can take one class, or combine them.
Introduction to Python Programming runs from February 2 – March 16, 2026. Students must register by February 10.
Machine Learning runs from March 2 – May 3, 2026. Students must register by March 10.
Each course costs $795 with a $35 registration fee.
No textbooks are required for any of the courses.
You will receive a certificate of completion after you successfully complete each course.
You may also request to receive a digital badge for each class that will be embedded with the competencies learned. This badge can be added to your resume, LinkedIn page, portfolio, or even shared with your current or future employer.
Karlan Schneider is a software engineer turned educator who’s passionate about making programming accessible and practical for new learners.
He spent over a decade building enterprise-level software in Java for organizations including the Interior Business Center and Comcast, where he led teams, mentored engineers, and architected large-scale systems. He completed his Master’s in Computer Science from the University of Denver in 2025 before transitioning into education.
He’s currently an adjunct professor at MSU Denver teaching Python programming, mobile app development, and machine learning. He loves helping students think critically about problems and understand concepts deeply, providing support and feedback that encourages growth through challenge. He’s committed to student success and helping learners build strong foundations in programming – not just syntax, but the problem-solving skills that transfer across languages and careers.
Dr. Ranjidha Rajan will be the instructor for this Introduction to Machine Learning course. She holds a doctoral degree in Learning Analytics and brings an interdisciplinary background that bridges data science, education, and technology. At MSU Denver, she teaches courses on data visualization, programming languages, and algorithms. Her research focuses on AI in education, learning analytics, and data visualization, with a special interest in how generative AI can enhance teaching, research, and student learning.
Please contact Brandy Schooler at 303-615-1234 or [email protected].
Phone: 303-615-1234
Office Location:
Jordan Student Success Building
3rd Floor – #330
Auraria Campus
Mailing Address:
MSU Denver
Innovative and Lifelong Learning
P.O. Box 173362
Campus Box 6
Denver, CO 80217-3362