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CER0-FDS - Certificate in Fundamentals of Data Analytics
Program Overview
Program Description
<p>This 12-credit-hour certificate is an enriching learning experience designed to equip participants with essential knowledge and skills in the foundational aspects of data science. This program is meticulously crafted for individuals eager to embark on a journey into the world of data analytics or those seeking to enhance their proficiency in core data science concepts. Throughout the program, participants will delve into key subject matter areas, including statistical analysis, data manipulation, and the fundamentals of machine learning. The curriculum places a strong emphasis on practical, hands-on learning, allowing participants to gain valuable experience through real-world projects and applications. This program will guide students through the intricacies of data science tools and techniques, with a focus on popular programming languages such as Python and R. By the end of the program, participants will have developed a solid understanding of the principles that underpin data science, empowering them to apply these skills in diverse professional settings. Whether students are beginner looking to build a strong foundation in data science or a professionals seeking to upskill, this program is tailored to meet their needs. Upon successful completion, participants will receive a certificate, validating their newfound expertise in the fundamentals of data science.</p>
Department(s)
Program Level
US
Program Code
CER0-FDS
Learning Outcomes
Assessment
Exams, quiz and homework that involves questions that assess data pre-processing, cleaning and handling missing data.
Justification
please see the attached file. All outcomes and assessment methods are listed in the pdf file too.
Name
Data Exploration and Cleaning:
Objective
Students will demonstrate ability to : explore and understand raw data sets, data cleaning and preprocessing techniques, handling missing data and outliers.
Assessment
Projects, exams, quizzes and homework that involves questions that tests theoretical knowledge of statistical concepts and meth- ods and data insights.
Name
Statistical Analysis:
Objective
Students will demonstrate: understanding of statistical concepts for data analysis, application of statistical methods to draw meaningful insights and decision making.
Assessment
Coding assignment and projects to evaluate pro ciency in pro- graming language and ability to implement machine learning models
Name
Programing and Tools
Objective
Students will demonstrate proficiency in programming language in data science such as R, python, SQL, power BI etc, mastery of popular data science libraries and frameworks such as pandas, numpy, scikit- learn.
Assessment
Assign assignment/projects that require creating visualizations. Assess the ability to produce visualizations based on criteria such as clarity, effectiveness, and the capacity to convey meaningful insights.
Name
Data Visualizations:
Objective
Students will demonstrate: proficiency in creating e ective visualiza- tions to show the the data insights, ability to use various visualization tools such as seaborn, matplotlib etc, ability to present an communicate data nd- ings e ectively.
Assessment
Evaluate the ability to process and analyze data e ciently in a distributed computing environ- ment. Assign questions that involve working with large-scale data using big data techniques.
Name
Big Data:
Objective
Students will demonstrate : familiarity with big data technologies such as hadoop and spark, ability to process and analyze large scale data.
Assessment
Assign work on datasets that ask students build and evaluate ma- chine learning models. Assess their ability to choose appropri- ate models and test the model performance.
Name
Machine Learning:
Objective
Students will demonstrate: basic understanding of machine learning algorithms and their applications, ability to implement and evaluate machine learning models, ability of model selection and validation techniques.
Assessment
Assess database querying skills through practical problems. Evaluate the ability to design and manage database for given scenarios. Present ethical case studies re- lated to data science and assess student ability to identify and ad- dress relevant issues. Evaluate awareness of privacy issues and adherence to responsible data practices.
Name
Database Management and Ethics:
Objective
Students will demonstrate : ability in working with database creation and management and SQL for data retrieval and manipulation, awareness of ethical consideration and pri- vacy issues in data science, understanding of responsible and fair use of data.