Data Analytics Using Python

Data Analytics Using Python

In this course, you will learn the rich set of tools, libraries, and packages that comprise the highly popular and practical Python data analysis ecosystem. This course is primarily taught via screen sharing programming videos. Topics taught range from basic Python syntax all the way to more advanced topics like supervised and unsupervised machine learning techniques.

Key topics:

• Installing Python/Jupyter/IPython on Windows and Mac
• Python Basics (variables, strings, simple math, conditional logic, for loops, lists, tuples, dictionaries, etc.)
• Using the Pandas library to manipulate data (filtering and sorting data, combining files, GroupBy, etc.)
• Plotting data in Python using Matplotlib and Seaborn
• Logistic Regression using Scikit-Learn
• Classification and Regression Metrics
• Decision Trees using Scikit-Learn
• Random Forests (Scikit-Learn)
• Clustering Algorithms (K-Means, Hierarchical Clustering)

Practical experience:

• Hands on programming assignments that are reviewed weekly via screen sharing videos
• Student's will be tasked to complete a final project, utilizing skills learned throughout the course

Course typically offered: Online, quarterly.
Currently offering two sections, online and Live Online.

Software: Students will use Python to complete hands-on assignments. These tools are free and open-source.

Prerequisites: Prior knowledge of the Python language is required for this course. Students should have completed Intro to Programming (Python) or Crash Course in Python for Data Analytics (CSE-41386) or have equivalent knowledge before taking this course.

Next steps: After completion of this course, students are encouraged to consider taking additional coursework in the Machine Learning Methods or Python Programming certificates.

Contact: For more information about this course, please contact unex-techdata@ucsd.edu.

Course Number: CSE-41204
Credit: 3.00 unit(s)
Related Certificate Programs: Business Intelligence Analysis, Data Mining for Advanced Analytics, Database Management, Geographic Information Systems, Python Programming, R for Data Analytics

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4/9/2024 - 6/8/2024

$750

Online

Closed

• SECTION ID:

  178476

• CLASS TYPE:

  Online Asynchronous.
  
  This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
  You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

• INSTRUCTOR:
  

  Mathapathi, Shivakumar

  Shivakumar Mathapathi MS, is the Adjunct Professor at Sonoma State University and Santa Clara University. He is the co-founder and CTO of Dew Mobility, USA, Team Lead for Global City team challenge hosted by the National Institute of Standards & Technology (NIST USA). Shivakumar has over 25 years of experience in product development, design and faculty. Mathapathi is a seasoned technologist, instructor and practitioner on the Internet of Things (IoT) with extensive experience as lead faculty, lab-practice and mentorship in executing smart city, smart agriculture, assisted living, and other IoT related projects. He has designed study programs and academic syllabi for the IoT course, a master’s curriculum taught at Santa Clara University and California Polytechnic State Unive...Read More

• TEXTBOOKS:

  No information available at this time.

• POLICIES:

  No refunds after: 4/15/2024.
  

• NOTE:

• DATE & LOCATION:

  4/9/2024 - 6/8/2024
  extensioncanvas.ucsd.edu
  You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.