IEEE Day 2025 Celebration - Workshop
🎉 This event is part of IEEE Day 2025 celebrations.
Join us in celebrating IEEE Day 2025 with an interactive webinar on Python & Machine Learning: From Basics to Applications.
This 2-hour hands-on session will introduce Python fundamentals, data analysis with NumPy & Pandas, visualization with Matplotlib, and the basics of machine learning (regression, classification, and model training). Participants will gain practical skills to analyze data, build simple ML models, and explore pathways to more advanced AI topics.
Open to students, engineers, researchers, and early-career professionals, this session is designed to make Python and ML accessible, practical, and inspiring.
Date and Time
Location
Hosts
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- 1009 Canton Avenue
- National Wind Institute
- Lubbock, Texas
- United States 79409
- Building: National Wind Institute
- Click here for Map
- Starts 02 October 2025 05:00 AM UTC
- Ends 15 October 2025 04:30 PM UTC
- No Admission Charge
Speakers
Mostafa of Texas Tech University
Python & Machine Learning: From Basics to Applications
👩💻 What you’ll learn:
✔️ Python basics (syntax, loops, libraries)
✔️ Data analysis with NumPy & Pandas
✔️ Quick visualizations with Matplotlib
✔️ Fundamentals of regression & classification
✔️ Hands-on demo: train and test an ML model in Python
✔️ Pathways to explore clustering & deep learning
Biography:
Dr. Mostafa Mohammadpourfard is an Assistant Professor specializing in cybersecurity and machine learning applications for renewable energy systems at Texas Tech University. He is a senior member of IEEE and joined TTU after serving as a Postdoctoral Researcher at Arizona State University, ranked 137th globally for Engineering & Technology by QS rankings. At ASU, his research focused on the cybersecurity of power grids, machine learning for security, and the cybersecurity of critical infrastructures. Prior to ASU, Dr. Mohammadpourfard held the prestigious Marie Skłodowska-Curie Fellowship at Istanbul Technical University, ranked 95th globally for Engineering & Technology, and an Assistant Professorship at Sahand University of Technology, a young university ranked within the 301-350th bracket in 2023 by Times Higher Education. Dr. Mohammadpourfard’s research blends technical rigor with impactful societal applications, particularly in sustainable energy systems and smart grid cybersecurity. His work has garnered significant funding, including $156K from the European Commission and $40,000 from a local power distribution company for projects in cybersecurity and AI within smart grids. He has also played a critical role as a principal contributor in drafting and submitting a $5M Department of Energy proposal focused on the cybersecurity of critical infrastructure, collaborating with prestigious institutions such as MIT, Georgia Tech, MITRE, NREL, and Sandia National Laboratories.
Dr. Mohammadpourfard has published over 30 peer-reviewed papers in top-tier journals and conferences and has extensive experience in interdisciplinary research. His expertise spans renewable energy cybersecurity, machine learning for security, network security, and cryptography. As an active reviewer, Dr. Mohammadpourfard has contributed to over 100 papers for esteemed journals, including IEEE Transactions on Information Forensics and Security, IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid and etc. His teaching experience includes developing and delivering courses in computer science and cybersecurity, such as Advanced Computer System Security, Data Mining, and Smart Grid Security, at institutions like Istanbul Technical University and Sahand University of Technology. Dr. Mohammadpourfard is passionate about fostering an inclusive and stimulating educational environment that encourages critical thinking and practical application. His experience with online teaching platforms and methodologies equips him to deliver engaging courses in a variety of formats. At TTU, he looks forward to developing new courses in renewable energy cybersecurity and expanding the curriculum to prepare students for emerging challenges in smart grid cybersecurity.
As a speaker, Dr. Mohammadpourfard has shared his insights at leading institutions and conferences worldwide, including Stanford University (USA), McGill University (Canada), and Uppsala University (Sweden), emphasizing the intersection of smart grids, cybersecurity, and machine learning.
Email:
Address:1009 Canton Avenue, National Wind Institute, Lubbock, Texas, United States, 79409
Agenda
Webinar Plan (2 Hours)
Title: Python & Machine Learning: From Basics to Applications
Audience: Engineers, researchers, students, early-career professionals in data/AI
Goal: Give participants a crash introduction to Python for data analysis, then show how machine learning solves real problems.
Learning Outcomes
By the end of this session, participants will:
- Be comfortable with Python basics (syntax, libraries, data handling).
- Use Pandas & NumPy for quick data analysis.
- Understand the intuition of regression & classification.
- Train and evaluate a simple ML model in Python.
- Know how to explore deeper topics like clustering & deep learning.
Timed Agenda (120 minutes)
00:00 – 00:05 | Welcome & Setup
- Poll: Python experience (none / beginner / intermediate).
- Share GitHub/Colab link with starter notebook.
00:05 – 00:25 | Python Basics Refresher
- Quick intro: syntax, variables, loops, functions.
- Libraries for ML: NumPy, Pandas, Matplotlib, Scikit-learn.
- Demo: Load a CSV, calculate summary statistics, plot a histogram.
00:25 – 00:55 | Data Analysis with Python
- Pandas: dataframes, filtering, grouping.
- NumPy: arrays, operations.
- Matplotlib: visualization basics.
- Hands-on mini demo:
- Load a dataset (e.g., student grades or Iris dataset).
- Clean missing values.
- Plot correlation heatmap.
00:55 – 01:35 | Machine Learning Fundamentals
- Concepts: Supervised vs. unsupervised learning.
- Regression: Predicting continuous values.
- Classification: Label prediction.
- Hands-on Demo (live in Colab):
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