The pathway below represents an efficient and effective course taking sequence for this program. Individual circumstances might require some changes to this pathway. It is always recommended that you meet with an academic counselor to develop a personalized educational plan.
The courses have been intentionally placed and should be prioritized in
the order
in which they appear. If you are unable to take all the courses in
a semester, you
should prioritize enrolling in the courses in the order below.
Some courses have
been noted as “Appropriate for Intersession” 
. Should you need (or want) to take
classes
in the summer and/or winter intersessions,
the program recommends these courses as appropriate for the condensed
schedule of
the intersessions.
Some pathways combine a “Certificate of Achievement” and an “Associate
Degree”. If
you are pursuing only the Certificate of Achievement, you are only
required to take
the courses marked “Program Requirement” 
.
All pathways include at least one “Gateway Course” 
which introduces you to the program and/or field of study and helps you
decide if you want to continue with this Academic and Career Path.
Most Associate degrees (though not Associate Degrees for Transfer)
require satisfying the SMC Global Citizenship requirement. If the Program
Requirements do not include a “Global Citizenship course” 
, be sure to select a General Education course that also satisfies Global Citizenship.
Effective Fall 2023
Data science is an applied field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from both structured and unstructured data sources. Data science incorporates data mining, machine learning and big data to make predictions and identify actions that organizations can take to be more effective. Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations. This certificate will prepare students for jobs in this field by providing students with skills in different technologies and techniques that are used for data science and machine learning. Students may also choose to transfer to four-year universities with established undergraduate programs in Data Science.
Upon completion of the program, students will:
- Upon completion of the program, students will be able to analyze data and employ different software tools to make certain predictions and optimize organizational operations.
Icon Key
-
Gateway Course
-
Program Requirement
-
General Education -
Appropriate for
Intersession
-
Available Online -
Global Citizenship
Semester 1
9 Units
In this course, students will explore the field of data science and the possible career pathway that can be taken. Students will learn how the data science process can be used to address real-world problems. The course will cover a basic introduction to the key areas of data science including data acquisition and management, data modeling, analysis visualization, and data reporting. Students will be introduced to tools to analyze and visualize data for data-driven decision making.
This course introduces students to Tableau, a popular platform for data visualization and simplification of complex data. It was designed to help the user to create visuals and graphics without the help of any programmer or any prior knowledge of programming. Topics include: connecting to different data types, exploring and analyzing the data visually, build custom calculations. Students will build a fully interactive dashboard, build a story to present and share the findings with publishing online or via Tableau server.
This is a beginning course intended for students who plan to take additional computer science courses. The course covers an introduction to programming concepts such as designing, coding and testing. Other concepts such as computer hardware, operating systems, compilers and databases are also discussed. The Internet and an introduction to cybersecurity and cloud computing are also included.
Semester 2
9 Units
In this course students will focus on the data science pipeline including problem formulation, data cleaning and preprocessing, exploration of data with visualization, model prediction and inference for decision making. Students will use different software tools and programming for each step of the data science pipeline, include data exploration and transformation, algorithms for machine learning concepts such as classification, regression, and clustering. In addition, students will learn how to effectively present any findings to an audience.
- Skills Advisory: CS 82A
This course introduces cloud computing which shifts information systems from on-premises computing infrastructure to highly scalable internet architectures. The course provides a solid foundation of cloud computing technologies and provides students with the understanding required to effectively evaluate and assess the business and technical benefits of cloud computing and cloud applications. Students analyze a variety of cloud services (storage, servers and software applications) and cloud providers. Case studies will be used to examine various industry cloud practices and applications. The course also surveys cloud careers and discusses industry demand for cloud skills.
- Prerequisite: CS 3
This course introduces the Python programming language. Students will learn how to write programs dealing in a wide range of application domains. Topics covered include the language syntax, IDE, control flow, strings, I/O, classes and regular expressions. Students may use either a PC (Windows) or a Mac (Linux) to complete their programming assignments.
- Skills Advisory: CS 3
- Area IV-B: Language and Rationality (Group B) Option 2
Semester 3
9 Units
This course builds on a first level course in Python exposing students to more advanced topics and applications to industry. Topics cover object-oriented programming, creating classes and using objects, web applications, and some common libraries and their functions used for data manipulation. Students may use either a PC (Windows) or a Mac (Linux) to complete their programming assignments.
- Skills Advisory: CS 87A
- Area IV-B: Language and Rationality (Group B) Option 2
This course will cover how business decisions can be made into machine learning problems for deeper business insight. We will cover the terms and concepts required to help you learn and build a good foundational understanding of machine learning, artificial intelligence and deep learning. You will learn the various Amazon Web Services Machine Learning stack, Artificial Intelligence and Deep Learning services, using application use cases, frameworks and infrastructure that will allow us to build, train, and deploy learning models at scale. Data is a vital part of machine learning, we will cover how business data is stored, moved and processed throughout the machine learning pipeline.
- Skills Advisory: CS 79A
In this course, students will learn how Machine Learning can yield deeper insights in different industry domains. Students will learn the various Azure tools and services for developing and deploying predictive solutions using Azure Artificial Intelligence, Machine Learning and Deep Learning. By using application use cases, frameworks and infrastructure, students will build, train, and deploy learning models at scale. Since data is a vital part of machine learning, we will cover how data is stored, moved and processed throughout the machine learning pipeline.
- Skills Advisory: CS 79A
R is a commonly used programming language for data analysis, data visualization, machine learning, and data science. In this course students will learn the fundamentals of R syntax, how to organize and modify data, prepare data for analysis, and create visualizations.
- Skills Advisory: CS 82A