BUS 48 — Practical Analytics: Transforming Data into Decisions
Quarter: Winter
Instructor(s): Moe Lotfy
Date(s): Jan 13—Mar 17
Class Recording Available: Yes
Class Meeting Day: Mondays
Grade Restriction: No letter grade
Class Meeting Time: 5:30—7:20 pm (PT)
Please Note: No class on January 20 and February 17
Tuition: $610
Refund Deadline: Jan 15
Unit(s): 1
Enrollment Limit: 40
Status: Open
Quarter: Winter
Day: Mondays
Duration: 8 weeks
Time: 5:30—7:20 pm (PT)
Date(s): Jan 13—Mar 17
Unit(s): 1
Tuition: $610
Refund Deadline: Jan 15
Instructor(s): Moe Lotfy
Grade Restriction: No letter grade
Enrollment Limit: 40
Recording Available: Yes
Status: Open
Please Note: No class on January 20 and February 17
Whether you are new to the job market or an established leader, converting data into actionable insights is a crucial business skill and the cornerstone of informed decision-making. This course will equip students with the knowledge and practical skills to navigate complex analytical challenges by teaching them how to interpret data and turn numbers into compelling narratives that inspire action and drive innovation.
The course is organized into two main sections. Section one focuses on analytics project scoping, data preparation, exploratory analyses, and conveying data findings through compelling visualizations. Students will learn to collect, clean, prepare, and visualize data for analysis while ensuring its quality. In section two, students will learn A/B testing frameworks used in practice, gain practical experience with statistical/machine learning techniques to extract complex patterns hidden in data, and build/deploy real-world end-to-end analytics and machine learning projects. The two sections will position students to become influential leaders capable of making decisions that foster innovation and help companies gain and maintain a competitive edge.
The course is organized into two main sections. Section one focuses on analytics project scoping, data preparation, exploratory analyses, and conveying data findings through compelling visualizations. Students will learn to collect, clean, prepare, and visualize data for analysis while ensuring its quality. In section two, students will learn A/B testing frameworks used in practice, gain practical experience with statistical/machine learning techniques to extract complex patterns hidden in data, and build/deploy real-world end-to-end analytics and machine learning projects. The two sections will position students to become influential leaders capable of making decisions that foster innovation and help companies gain and maintain a competitive edge.
MOE LOTFY
Data Science and Analytics Leader
Moe Lotfy has over a decade of experience in data science and engineering, spanning industry, research, and academia. He has held senior analytics and leadership positions at companies such as Tesla, Hulu/Disney, and KPMG, where he built and led functions in engineering, experimentation, marketing, and financial services. He received a PhD in mechanical and nuclear fusion engineering from UCLA and a BSc in mechanical engineering from the University of Illinois Urbana-Champaign. Lotfy is equally passionate about education, having developed and taught data science and AI courses on leading platforms with more than 10 million learners. Textbooks for this course:
There are no required textbooks; however, some fee-based online readings may be assigned.