Data Structures, Data Mining with Python
Unlock new career opportunities by delving deeper into the world of data science. This online course is the third part in our Professional Concentration in Python for Data Science, Web and Core Programming and is designed for professionals looking to develop relevant software skills in general or switch to a technical career in data science or software engineering.
Data Structures and Data Mining with Python will introduce advanced Python programming features, with an emphasis on cloud computing, to solve large data problems. Lectures, group discussions and hands-on activities will allow you to explore how the Python built-in data structures such as lists, dictionaries and tuples can be used to perform increasingly complex data analysis while creating regression and cluster models for data mining. This course will cover topics such as ETL with command line interface, Docker, functional programming, MapReduce framework and Spark with Spark ML. You will gain practical experience with Amazon Web Services Elastic Computing, Elastic MapReduce and Google Cloud Computing
Learning Outcomes
- Apply Python advanced language features to write efficient programs
- Use advanced Python Data Structures for efficient handling of data
- Access and manipulate data from SQL databases (MySQL) using Python connectors
- Analyze data with Python PANDAS
- Understand and implement MapReduce in Python
- Use big data frameworks like Hadoop in Python for big data analysis and analytics
- Use machine learning concepts in AWS EMR
Skills You’ll Gain
- Data analysis in Python
- Writing efficient programs
- Using advanced tools in Python
Section Notes
This is an online course with class materials that can be accessed throughout the week. The course is structured to move from one week to the next.
Access to the online course platform, Canvas, will be granted to students one business day before the scheduled start date of the course.
Students pursuing the full Professional Concentration in Python for Data Science, Web and Core Programming must earn a grade of C or higher (not a C minus) in order for this course to count towards the requirements for the Professional Concentration. Courses applied towards the Professional Concentration in Python for Data Science, Web and Core Programming must be completed within five years.
Refund Deadline: May 13, 2024. Refunds and/or enrollment transfers will not be approved after this date.
Enrollment Policies
Click here or visit https://cpe.ucdavis.edu/student-services/withdrawals-refunds-and-transfers to view complete enrollment policy information including details on withdrawals and transfers.
Refund Deadline: May 13, 2024. Refunds and/or enrollment transfers will not be approved after this date.
Prerequisites
Intermediate Python (Course Number: 508128)