Catalog Description: The certificate expands the Data Analytics Certificate of Achievement by providing students with more advanced skills in Data Science tools such as Machine Learning, and Deep Learning. The Data Science certificate presents a more robust preparation for work within Data Science teams at various organizations. Students learn to use Cloud-based tools to manage, wrangle, and analyze data, and to use Python libraries to draw statistical inferences, which solve real-world problems.
Course Requirements:
CS 119 - Programming in Python
CIS 192 - Introduction to Cloud Computing
CIS 193 - Database Essentials in AWS
Prerequisite: CIS 192. Advisory: CO SCI 434 or CIS 219.
CIS 194 - Compute Engines in AWS
Prerequisite: CIS 192
CIS 219 - Introduction to Oracle: SQL and PL/SQL
CIS 124 - Data Analytics-Advanced Excel and Access (3)
CS 121 - Python Programming for Data Science (3)
Prerequisite: CS 119
CS 159 - Foundations of Data Science
Prerequisite: NONE
Core Required Courses:
CS 165 - Data Science Programming and Applications (3)
Prerequisites: CS 121, CIS 193, CS 159
CS 166 - Machine Learning Programming and Applications (3)
Prerequisites: CS 121, CIS 194, CS 159
Learning Outcomes:
Upon completion of the program, students will be able to:
Utilize cloud database systems on AWS, as well as Oracle, and Access in order to manage databases, and respond dynamically to information and computing technology workloads
Wrangle data using Excel, and Python libraries in order to communicate summaries of data using multiple representations including graphs, tables, numerical summaries, and words
Identify Statistical methods, and models that represent, and describe real world data, and draw inferences that solve real-world problem using Python libraries
Use advanced Python libraries, and the AWS web services in order to develop Supervised, and Unsupervised learning models, and to recommend data-driven actionable insights for Business, and Marketing problems
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Occupational skills, and employment. The goal is to obtain employment within entry-level Data Analytics careers.
Data Science careers demand the ability to manage, and wrangle data, and to be able to utilize it in a way that helps answer industry-related questions. The program tackles these skills first with a set of courses that introduce cloud-based tools for managing, and wrangling data with AWS, SQL, and Access, and analytical computational tools such as Excel, and Python libraries such as Pandas, Numpy, SciPy, Matplotlib over the Jupyter notebook; and finally students develop knowledge of basic statistical techniques, and models that provide the foundations for understanding how to select the appropriate models, and techniques in order to provide real-world solutions.
The Data Science certificate build on the Data Analytics Certificate of Achievement by providing students with more advanced skills in Data Science tools such as Machine Learning, and Deep Learning. Students use Cloud-based tools to develop Supervised, and Unsupervised Learning models, and solve real-world problems.
Course | Title | Units | Year/Semester (Y1 or S1) |
---|---|---|---|
CIS 192 | Introduction to Cloud Computing | 3 | S1 |
CIS 193 | Database Essentials in Amazon Web Services | 3 | S1 |
CIS 194 | Compute Engines in Amazon Web Services | 3 | S1 |
CS 119 | Programming in Python | 3 | S1 |
CIS 219 | Introduction to Oracle: SQL & PL/SQL | 3 | S2 |
CIS 124 | Data Analytics - Advanced Excel and Access | 3 | S2 |
CS 159 | Foundation of Data Science | 3 | S2 |
CS 121 | Python Programming for Data Science and Machine Learning | 3 | S2 |
CS 165 | Data Science Programming and Applications | 3 | S3 |
CS 166 | Machine Learning Programming and Applications | 3 | S3 |
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