BUS 48 — Practical Analytics: Transforming Data into Decisions
Quarter: Spring
Instructor(s): Moe Lotfy
Date(s): Apr 2—Jun 4
Class Recording Available: No
Class Meeting Day: Tuesdays
Grade Restriction: No letter grade
Class Meeting Time: 5:30—7:20 pm (PT)
Tuition: $715
Refund Deadline: Apr 4
Unit(s): 2
Enrollment Limit: 40
Status: Closed
Quarter: Spring
Day: Tuesdays
Duration: 10 weeks
Time: 5:30—7:20 pm (PT)
Date(s): Apr 2—Jun 4
Unit(s): 2
Tuition: $715
Refund Deadline: Apr 4
Instructor(s): Moe Lotfy
Grade Restriction: No letter grade
Enrollment Limit: 40
Recording Available: No
Status: Closed
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 AB testing frameworks used in practice, gain practical experience with statistical/machine learning techniques to extract complex patterns hidden in data and explore two aspects of responsible AI: data bias and privacy by design. 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 AB testing frameworks used in practice, gain practical experience with statistical/machine learning techniques to extract complex patterns hidden in data and explore two aspects of responsible AI: data bias and privacy by design. 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
Analytics Leader
Moe Lotfy is an analytics leader with over a decade of experience in data science and engineering, spanning research, academia, and industry. He has held senior analytics positions at companies such as Hulu/Disney and KPMG, where he built and led functions in 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.