Fundamentals of Data Science
An ever-increasing volume of research and industry data is being collected on a daily basis. Skilled data scientists are needed to process and filter the data, to detect new patterns or anomalies within the data, and gain deeper insight from the data.
This course provides students with a foundation in basic data mining, data analysis, and predictive modelling concepts and algorithms. Using practical exercises, students will learn data analysis and machine learning techniques for model and knowledge creation through a process of inference, model fitting, or learning from examples.
Practical experience:
- Hands-on data mining projects
Software: Python is used for class assignments. There is no additional cost for this product.
Course typically offered: Online in Fall and Spring
Prerequisites: Before enrolling in the course, students need to have prior knowledge of statistics for data analytics or equivalent practical experience, as well as a basic understanding of the Python Programming Language. For students who do not have knowledge of statistics for data analytics, it is recommended to take the Statistics for Data Analytics, Introduction to Statistics or Linear Algebra for Machine Learning course. You can test your level of statistical knowledge by taking the online Self-Assessment quiz. For students who do not have basic knowledge of Python programming language, it is recommended to take Introduction to Programming course.
Next Steps: Upon completion of this course, consider taking other courses in Machine Learning Methods program to continue learning.
More Information: For more information about this course, please contact unex-techdata@ucsd.edu.
Course Number: CSE-41258
Credit: 3.00 unit(s)
Related Certificate Programs: Data Mining for Advanced Analytics, Machine Learning Methods
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4/2/2024 - 6/1/2024
$725
Online
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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.
Sipes, Tamara, Data Mining Specialist
Tamara Sipes is a data mining specialist. She uses her data mining expertise to analyze data, select meaningful attributes and build predictive models that discover significant trends and relationships. Her work has led to patent awards for clients in biotechnology and other industries, and she has published research in the areas of data mining and learning technologies.
INSTRUCTOR:
Wolter, Nicole, Research Program Analyst, San Diego Supercomputer Center, UC San Diego
Nicole Wolter has over 10 years of experience in high performance computing. She has spent six years doing research in performance modeling and characterization at UC San Diego. She has excellent analytical and model development skills most recently applied in the areas of medical informatics, sports analytics and large data analysis. She has conducted a number of data mining classes and lectures.
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POLICIES:
No refunds after: 4/8/2024.
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4/2/2024 - 6/1/2024
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.
There are no sections of this course currently scheduled. Please contact the Science & Technology department at 858-534-3229 or unex-sciencetech@ucsd.edu for information about when this course will be offered again.