AI & Optimization Crash Course Series 19-30 October, 2020

Join us for the upcoming online event, a series of workshops covering various topics in AI and optimization. The courses are introductory and no prior knowledge is assumed. Also, you will be entered in a random draw to win one of six $25 gift cards. Full information on the courses can be found below. All courses will be followed by a 30-minutes socialization and Q&A session. Registration is free but required for all participants. Before the start of each course, a Zoom link will be sent out to the email provided in the registration form.

Click here for registration.

Python Basics
October 19th at 5-6 pm EDT (GMT -4)
Instructor: Moira MacNeil (Email)


    • Introduction to dynamic languages
    • Variable types
    • Flow control
    • Functions, modules, and classes (including some useful existing modules)

Data Engineering in Python
October 20th at 5-6 pm EDT (GMT -4)
Instructor: Aida Khayatian (Bio)


    •  Python libraries for data analysis
    •  Reading data
    • Inspecting and aggregating data with Pandas
    • Exporting data with Pandas

Data Science in Python
October 21st-22nd at 5-6 pm EDT (GMT -4)
Instructor: Javad Soltani Rad (Bio)

‌‌Day 1 topics:

    •  Data visualization in Python
    •  Introduction to Machine Learning (ML)
    • Preparing data for ML models
    • Classification example in Python

Day 2 topics:

    •  Regression example in Python
    •  Unsupervised Learning (clustering) example in Python
    • Introduction to Deep Learning
    • Python tools for industrializing ML applications

Reinforcement Learning
October 26th-27th at 5-6 pm EDT (GMT -4)
Instructor: Peyman Kafaei (Bio)

Day 1 topics:

    •  Reinforcement Learning (RL) vs Supervised/Unsupervised Learning
    •  Introduction to RL
    • Markov decision processes
    • Elements of RL

Day 2 topics:

    • Model free prediction and control
    • Monte Carlo methods
    •  Temporal difference learning
    • Tabular mehtods vs approximation methods

Operations Research in Python
October 28th-29th at 5-6 pm EDT (GMT -4)
Instructor: Maryam Daryalal (Bio)

Day 1 topics:

    • Install and setup Gurobi in Python
    • Solve a linear programming model with Gurobi
    • Input/output management
    • Model modification
    • Warm start for LP/IP models
    • Handling infeasibility

Day 2 topics:

    •  Branch & bound for IP models
    •  Callbacks in branch and bound
    •  Access to information of nodes while solving
    •  Modify the model during solve
    • A sneak peek at Column Generation in Gurobi