Python for Data Analytics

  • course details
  • Dates and time: 6 – 8:30 p.m., Tuesdays and Thursdays, Mar 18 - April 3, 2025
  • Format: Online, instructor-led live sessions on Zoom
  • Number of sessions: 6
  • Instructional fee: $745, reduced fees available (see Cost section below for details)

In today’s fast-paced world, we need tools that not only handle large datasets but also automate repetitive workflows to save time and boost productivity. This intermediate-level Python course focuses on equipping you with the essential skills to analyze, visualize, and automate data processes.

Designed specifically for professionals, this course blends practical coding techniques with real-world applications, empowering you to turn raw data into actionable insights with ease.

Prerequisite: Knowledge of Python programming.

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What you will learn

  • How to work with Python’s advanced data structures
  • How to analyze data effectively using NumPy and Pandas
  • How to present data insights with Matplotlib and Seaborn
  • How to automate repetitive tasks such as data extraction, processing, and reporting

Who should attend

This course is ideal for professionals who already have a foundational understanding of Python and are eager to take their skills to the next level. Whether you're an engineer, a researcher, or a manager, if you’re looking to expand your Python expertise into data analysis, visualization, and automation, this course is for you!

Course content

A typical course covers the following:

  1. Advanced data structures in Python
    • Named Tuples, Double-Ended Queues, Counters, Ordered Dictionaries, etc.
  2. Foundations of Data Analysis with NumPy
    • Creating NumPy arrays, slicing and reshaping arrays, data types and conversions, mathematical and statistical functions
  3. Data Manipulation with Pandas
    • Series and DataFrames, data cleaning, applying functions, Groupby operations and aggregations
  4. Visualizing Data with Matplotlib and Seaborn
    • Line plots, bar charts, scatter plots, histograms, box plots, heatmaps, pair plots, and violin plots
  5. Automating Data Workflows with Python
    • Reading/writing CSV and Excel files with Pandas, basics of Web Scraping, automated creation of reports and visualizations, sending automated emails, scheduling tasks
  6. A complete data analytics project
    • Selecting a dataset and defining objectives, cleaning and preparing the data, performing exploratory data analysis (EDA), visualizing the patterns, exporting and presenting the results

Applied learning model

  • In- class examples and exercises focused on real-world tasks
  • A variety of “take home” problems to (optionally) practice between classes

Student materials

  • Course materials will be provided electronically
  • All required software is available for download for free
  • You will need an environment with Python 3.9
  • Setting up such an environment will be covered during the first class

Instructor

Aref Majdara

Aref Majdara received his Ph.D. from Michigan Technological University. Currently, he is an assistant professor of Electrical Engineering at Washington State University Vancouver. He teaches a wide range of Electrical Engineering and Computer Science courses. His areas of interest include machine learning, density estimation, and embedded systems.

Cost

The instructional fee is $745. There are limited number of seats available for employees of small businesses with fewer than 150 employees ($445), non-profits and educational institutions ($298), and for current WSU students ($90) and employees ($298). All instructional fees are per person and include a nonrefundable administrative fee of $75. See Registration for details.

The registration fee is the same regardless of residence.


Meetings and format

The course is delivered via Zoom videoconference with live instruction. To attend, you need a computer with webcam, microphone and high-speed internet.

Each Zoom session allows for live interactions with the instructor and other students via chat, web conferencing or phone, all in real time. Assignments and other materials will be available online through a web-based learning management system.

Certificate completion

  • Attend at least 5 of 6 sessions