Data Science & Machine Learning
Is your student interested in a potential academic major or career in data science machine learning? Professionals in these fields work on training and deploying mathematical models of all kinds to solve real-world problems.
Program Highlights
Residential Tuition:
$5,998
Commuter Tuition:
$3,298
Session 2:
June 22, 2025
July 4, 2025
Session 4:
July 6, 2025
July 18, 2025
Session 6:
July 20, 2025
August 1, 2025
Berkeley
Berkeley, CA
Course Overview
Did you know that data scientists hold some of the highest-paying jobs for students graduating with a bachelor’s degree in the United States? With the booming influence of data science and machine learning more job roles and opportunities are available in this industry than ever before. From improving decision making processes to releasing innovations, data has become essential to the success of nearly every industry.
In this program, students will cover a wide range of topics from Python basics to advanced concepts like neural networks and deep learning. Students will also have an opportunity to practice their learning by applying their knowledge through projects and exercises using real-world datasets. They will gain experience with popular data science and machine learning libraries such as pandas, scikit-learn, and TensorFlow. Students will also have discussions on the ethical implications of data science and artificial intelligence to prepare them to be responsible practitioners in the field.
Meet your instructor
Dr. Kamal Ali
Session 2 & 4
Dr. Kamal Ali is a distinguished AI and machine learning expert with over two decades of pioneering experience in Silicon Valley, where he currently serves as an industry consultant specializing in large language models, artificial intelligence, and conversational agents. He earned his Ph.D. and Master's in Computer Science from UC Irvine and he holds his BS in Computer Science from the University of Sydney. He has held several pivotal leadership roles including Chief Data Scientist at Simplifai, Machine Learning Scientist at Apple, Inc and Fusemachines, and was a co-founder and Chief Scientist of Peerlyst. His impressive career also includes serving as a Senior Research Scientist at Stanford University's prestigious Computational Learning Lab and he has over 30 peer reviewed papers and 3,000 citations.
Hanieh Haeri, PhD
Session 6
Hanieh is a seasoned Data Scientist based in the San Francisco Bay Area, holding a Ph.D. in Engineering from the University of California, Davis. She’s passionate about applying cutting-edge technologies to drive data-informed decisions and craft intelligent strategies across industries. Her work focuses on bridging the gap between industry and AI, with a particular emphasis on developing interpretable and responsible AI models. She’s deeply interested in the applications of computer vision and generative AI, and is motivated by the challenge of turning these advanced technologies into real-world solutions that create meaningful impact. She specializes in integrating AI and big data with modern geospatial technologies to solve complex spatial problems. Her experience spans building scalable data pipelines, predictive modeling, and designing intelligent geospatial applications to support strategic decision-making. With a strong foundation in data science and a passion for Earth science, she’s especially driven by projects that assess the environmental and societal impacts of spatial data. From urban infrastructure analysis to equitable resource distribution, she strives to deliver insights that promote sustainability and social good. As geospatial technology continues to transform industries, she’s committed to shaping its future through machine learning, innovation, and responsible AI practices.