Duration : 12 months

Programme Overview:

The Certificate in Data Science is a comprehensive program designed to equip students with the knowledge and skills necessary for a career in the field of data science. The certificate consists of four trimesters, each focusing on key areas of data science.

Trimester 1 introduces students to the field of data science and establishes a solid foundation for further study. Students will learn about the basics of data science, including an introduction to the field, Python programming for data science, data wrangling and cleaning, and exploratory data analysis. These modules provide essential knowledge and skills for understanding data manipulation, analysis, and visualization.

Trimester 2 builds upon the foundation laid in the first trimester and delves into more specific areas of data science. Students will study statistical methods for data science, gaining a deeper understanding of statistical techniques used in data analysis. They will also learn about machine learning fundamentals, exploring algorithms and techniques used to build predictive models. Additionally, the modules on data visualization and communication and big data analytics provide students with the skills necessary for effectively communicating data insights and working with large datasets.

In Trimester 3, students deepen their understanding of data science by focusing on advanced topics. They will study advanced machine learning techniques, delving into advanced algorithms and methodologies used in machine learning. The module on deep learning and neural networks introduces students to the concepts and applications of deep learning, a subset of machine learning that focuses on neural networks. The natural language processing module explores techniques for analyzing and understanding human language data. Additionally, students will study time series analysis, which involves analyzing and forecasting data that is collected over time.

Trimester 4 covers additional important aspects of data science. Students will study recommender systems, which involve developing algorithms that can provide personalized recommendations to users. The module on data mining and knowledge discovery introduces students to techniques for discovering patterns and extracting knowledge from large datasets. They will also learn about Bayesian statistics and probabilistic modeling, which involve using probabilistic methods for data analysis and modeling. Finally, the ethical and responsible data science module emphasizes the ethical considerations and responsible practices in handling and analyzing data.

After completing the Certificate in Data Science, students will have acquired a comprehensive set of skills and knowledge in data science. They will be equipped to work as data scientists, data analysts, or pursue further studies in the field. The certificate program provides a solid foundation for a successful and fulfilling career in the rapidly growing field of data science, addressing the increasing demand for professionals who can extract insights and value from data to drive informed decision-making.

Year 1 Trimester 1

Code	Description	Credit
DS1101	Introduction to Data Science	12
DS1102	Python Programming for Data Science	12
DS1103	Data Wrangling and Cleaning	12
DS1104	Exploratory Data Analysis	12

Year 1 Trimester 2

Code	Description	Credit
DS1105	Statistical Methods for Data Science	12
DS1106	Machine Learning Fundamentals	12
DS1107	Data Visualization and Communication	12
DS1108	Big Data Analytics	12

Year 1 Trimester 3

Code	Description	Credit
DS1109	Advanced Machine Learning Techniques	12
DS1110	Deep Learning and Neural Networks	12
DS1111	Natural Language Processing	12
DS1112	Time Series Analysis	12

Year 1 Trimester 4

Code	Description	Credit
DS1113	Recommender Systems	12
DS1114	Data Mining and Knowledge Discovery	12
DS1115	Bayesian Statistics and Probabilistic Modeling	12
DS1116	Ethical and Responsible Data Science	12