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Course

Data Science and Practical Applications

CSE-41401

This interactive course aims to equip students with an in-depth comprehension of data science principles and methodologies, with a strong emphasis on practical applications. Participants will develop tangible skills and hands-on experience in utilizing data science methods to derive significant insights from varied datasets. Encompassing topics such as data analysis, data engineering, machine learning, data visualization, and business analytics, the course primes students for real-world challenges across diverse industries.
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Course Learning Highlights:

  • Python Programming - Data Science Libraries
  • Data Analysis - Pandas for Python, Exploratory Data Analysis (EDA) techniques
  • Data Visualization - Visualization tools and techniques, Matplotlib and Seaborn
  • Data Engineering - Tools and techniques
  • Machine Learning - Supervised Learning and unsupervised learning, Model evaluation and hyperparameter tuning
  • Business Analytics - Descriptive analytics, Predictive analytics, Healthcare analytics, Improving decision-making skills

Course Learning Outcomes:
  • Learn to apply statistical methods to address a variety of real-world problems
  • Manipulate extensive datasets to prepare them for thorough data analysis
  • Evaluate data visualizations based on their design effectiveness
  • Learn to analyze data using different techniques and algorithms
  • Implement algorithms in real-world scenarios, refine obtained models, and report on predicted accuracy using these models
 
Software: Anaconda Navigator will be used
 
Hardware: A computer with a multi-core processor, with 16GB RAM memory and minimum 512GB SSD of storage
 
Course Typically Offered: Online in Spring
 
Prerequisite: Previous knowledge of Python, Calculus I, Linear Algebra and Statistics or equivalent is required before taking this course
 
Next Steps: Upon completion, consider additional coursework in our specialized certificate in Machine Learning Methods to continue learning
 
Contact: For more information about this course, please contact unex-techdata@ucsd.edu

Course Information

Online
3.00 units
$795.00

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Course sessions

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Section ID:

187201

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.

Textbooks:

All course materials are included unless otherwise stated.

Policies:

  • No refunds after: 4/7/2025

Schedule:

No information available at this time.
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Instructor: Ganesan Narayanasamy

Ganesan Narayanasamy
Ganesh Narayanasmy holds a Masters degree in Computer Science and is Global Technology Enablement award winner. He in is a global leader in academia and research. He is a Founder and Investor in Technology Businesses. As a senior leader at IBM for almost three decades, Ganesan is well-known for his contributions to chip design, artificial intelligence, and high-performance computing. He has led the WW Academia team for OpenPOWER chip to Solutions stack and organized the development of the OpenPOWER Ecosystem, which includes AI/ML/Cloud solutions, establishing centers of excellence for AI and Chip Design labs, Industry Hubs, and Technology labs, among other initiatives. Ganesan is always enthusiastic about collaborating on the development of creative solutions utilizing cutting-edge technology with industries, partners, universities, and research institutes. Additionally, he has created specialized courses and curricula with special hardware access for Chip Design and Data Science/AI.
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