Introduction to Data Science This course provides a comprehensive introduction to Data Science, covering fundamental concepts, tools, and techniques. You’ll explore how data is collected, processed, analyzed, and visualized to make data-driven decisions. Whether you're new to data science or looking to strengthen your foundational knowledge, this course will equip you with essential skills for working with data. By the end of this course, you will have a clear understanding of data science workflows, machine learning basics, and how data-driven insights drive decision-making in various industries. MODULES Module 1: Introduction to Data Science Module 2: Data Collection & Processing Module 3: Exploratory Data Analysis (EDA) Module 4: Introduction to Machine Learning Module 5: Careers in Data Science LEARNING OUTCOMES. By the end of this course, learners will: 1) Define Data Science and understand its role in modern industries. 2) Explain key Data Science concepts, including data wrangling, exploratory data analysis (EDA), and machine learning. 3) Identify common tools and programming languages used in data science (Python, R, SQL). 4) Understand data collection, cleaning, and preprocessing techniques. 5) Perform basic exploratory data analysis (EDA) using Pandas and Matplotlib. TARGET AUDIENCE This course is ideal for: 1) Beginners interested in starting a career in Data Science. 2) Students or professionals transitioning into a data-driven role. 3) Business professionals looking to leverage data for decision-making. 4) Tech enthusiasts curious about AI, machine learning, and analytics. PREREQUISITE :Nil COURSE DURATION: 3-4 Hours ASSESSMENT TYPE: Practice Assessment with MCQ IS A CERTIFICATE OF COMPLETION PROVIDED AFTER THE COURSE: Yes.