Advanced Python Packages for Business Analytics
100% ONLINE
SELF-PACED
NO COST
Summary
This is a hands-on, fully online, self-paced workshop that covers advanced Python for data analysis and machine learning. It is assumed that you have already successfully completed the Basic Python Programming Workshop or have a basic understanding of Python as a Programming Language.
Duration: 4 weeks
Location: Online
Modality: Self-paced
This Course is not for Academic Credit
What you'll learn:
Learners will become familiar with advanced Python packages used for the end-to-end data analysis life cycle, including: NumPy, Pandas, SKLearn, regex, spaCy, Matplotlib, Pandas, and Seaborn.
Module and Content:
This workshop consists of ~15 hours of recorded content, 7 exercise sets, and 4 (multiple-choice) quizzes. Students should expect to spend 5-10 hours per week for 4 weeks to fully benefit from the course material.
Learning Objectives:
In this workshop, you will accomplish the following goals:
- Examine the use of advanced list manipulation techniques, including list comprehension, lambda functions, map functions, and filter functions.
- Experiment with creating, using and manipulating data in NumPy.
- Outline how to create, use and manipulate data in Pandas, as well as learn how to accomplish SQL like operations in Pandas.
- Evaluate the use of the SKLearn framework to build machine learning models.
- Demonstrate how to use SKLearn libraries to Preprocess data, build supervised and unsupervised models, as well as use advanced SKLearn features such as pipelines, column transformers, cross-validation and grid search.
- Perform text manipulation using two powerful regex and spaCy.
- Visualize data using three different Matplotlib, Pandas, and Seaborn.
Who is this certificate designed for:
Computer Systems Engineer BSE or Computer Science BS major; CSE 310 with C or better; CSE 230 or EEE 230 with C or better OR CSE graduate student OR Visiting University Student.
What you'll receive:
Upon finishing this certificate, students will receive an online certificate of completion.
Meet the instructor:
Hina Arora, PhD
Clinical Associate Professor, W.P. Carey Information Systems Arizona State University
Hina Arora is a Clinical Assistant Professor and Director of Experiential Analytics in the W. P. Carey School of Business at Arizona State University. At ASU, Hina has taught advanced data mining courses at the undergraduate and graduate levels, held multiple service roles, and consulted. Prior to joining ASU, Hina was a Group Manager at Microsoft, where she led analytics teams in the Windows Services Division and the US Central Marketing Organization. She has also held Software Development positions at IBM and Cognizant, and worked as a Research Scientist at the Center for Excellence in Document Analysis and Recognition at SUNY Buffalo. Hina has a PhD in Information Systems, a Masters’ degree in Electronics Engineering, and an Undergraduate degree in Physics.