Graduate Certificate in Data Science (Applied)

Program Overview

The Graduate Certificate in Data Science (Applied) is an online program that equips professionals with the skills needed in the data-driven job market. The program covers data science principles, analytics tools, and practical applications. Graduates gain proficiency in data analysis, model building, and data visualization, preparing them for careers as data analysts, business data analysts, and management analysts.

Program Outline

Degree Overview:

The Graduate Certificate in Data Science (Applied) is a comprehensive online program that empowers professionals with the highly sought-after skills needed in today's data-driven job market. This part-time program spans 8 months and provides a flexible learning experience that aligns with the demands of a modern workplace.

Objectives:

The program aims to equip individuals with a comprehensive understanding of data science principles and their practical applications within various professional domains. Graduates will gain proficiency in evaluating and utilizing industry-leading analytics tools and techniques to effectively address real-world data-related challenges.

Program Description:

This flexible online program seamlessly blends intensive and blended learning modes to deliver an immersive and engaging educational experience. Students will delve into the fundamentals of data science, exploring its role as a strategic process within organizations. They will acquire hands-on knowledge of the discipline's technical practices and develop critical thinking skills to analyze and interpret data with accuracy. The program emphasizes the practical implementation of data science techniques, ensuring graduates possess the confidence and competence to leverage data for informed decision-making and organizational improvements.

Outline:

Module 1: Introduction to Data Science

Students will gain an overview of the field of data science, including its principles, methodologies, and applications. Key topics covered include data types, data collection techniques, and data exploration methods.

Module 2: Data Wrangling and Preprocessing

This module focuses on the essential skills of data cleaning, manipulation, and preparation. Students will learn to manage missing values, identify and correct data errors, and transform data into a usable format for analysis.

Module 3: Statistical Analysis

Students will explore fundamental statistical concepts and techniques, including descriptive statistics, probability distributions, hypothesis testing, and regression analysis. These methods provide a solid foundation for understanding and interpreting data patterns and relationships.

Module 4: Machine Learning

This module introduces the principles and algorithms of machine learning, enabling students to develop predictive models that can identify patterns and make accurate predictions from data.

Module 5: Data Visualization

Students will learn to effectively communicate data insights through compelling visualizations. Topics covered include data visualization principles, choosing appropriate chart types, and creating interactive visualizations using industry-standard software.

Assessment:

The program employs a range of assessment methods to evaluate student learning and progress. These assessments include:

Assignments:

Regular assignments assess students' understanding of course concepts and their ability to apply data science techniques to solve real-world problems.

Projects:

Hands-on projects provide opportunities for students to demonstrate their proficiency in data analysis, model building, and data visualization.

Examinations:

Final examinations test students' comprehensive knowledge and understanding of the program's content and their ability to apply data science principles to practical scenarios.

Teaching:

The program is delivered by a team of experienced industry professionals and academic experts who bring their specialized knowledge and practical experience to the classroom. The teaching approach is highly interactive and collaborative, fostering a supportive learning environment where students can actively engage with the material and with their peers.

Careers:

Graduates of the Graduate Certificate in Data Science (Applied) are well-prepared for a wide range of roles in the rapidly growing field of data science. Common career paths include:

Management Analyst

Business Data Analyst

Data Analyst

These professionals contribute to data-driven decision-making, analyze business trends, and extract meaningful insights from large datasets in various industries, including finance, healthcare, retail, and technology.