A data scientist is a skilled professional responsible for collecting, cleaning, analyzing, and interpreting large volumes of data to derive actionable insights that support business decision-making. They employ statistical methods, machine learning algorithms, and various data processing tools to explore data, build predictive models, and validate results. Data scientists also develop scalable data pipelines, ensure data quality, and create visualizations and dashboards to communicate findings effectively. Their role spans across understanding business requirements, designing data strategies, implementing algorithms, deploying models into production environments, and continually monitoring and refining those models to adapt to changing data patterns. Overall, a data scientist bridges the gap between raw data and strategic insights, empowering organizations to make informed, data-driven decisions.
25-08-2026 to 25-12-2026
SSC/Q8104/NSQF Level: 6
Duration
8 hrs
This module introduces the fundamental concepts of Artificial Intelligence & Big Data Analytics – An Introduction. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
16 hrs
This module introduces the fundamental concepts of Basic Statistical Concepts. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
24 hrs
This module introduces the fundamental concepts of Advanced Statistical Concepts. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
16 hrs
This module introduces the fundamental concepts of Statistical Tools and Usage. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
80 hrs
This module introduces the fundamental concepts of Importing Data. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
144 hrs
This module introduces the fundamental concepts of Pre-processing Data. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
24 hrs
This module introduces the fundamental concepts of Exploring Data. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
This module introduces the fundamental concepts of Data Structures and Algorithms. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
: This module introduces the fundamental concepts of Graph Algorithms. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
This module introduces the fundamental concepts of String Algorithms. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
This module introduces the fundamental concepts of Neural Networks. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
This module introduces the fundamental concepts of Programming for Data Science. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
24 hrs
: This module introduces the fundamental concepts of Applications of Pre-designed Algorithms. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
24 hrs
This module introduces the fundamental concepts of Inclusive and Environmentally Sustainable Workplaces. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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Duration
8 hrs
This module introduces the fundamental concepts of Introduction to Employability Skills. It explains the key ideas, practical applications, and importance of the subject in data science. Learners develop theoretical understanding and basic practical skills through examples and exercises.
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