Introduction to Data Science and Visualization

Introduction to Data Science and Visualization

Transcript

1. Shri. ShamraoPatil (Yadravkar) Educational & Charitable Trust’s Sharad Institute of Technology, College of Engineering Yadrav- (Ichalkaranji) (An Autonomous Institute) NBA Accredited Programmes, NAAC ‘A’ Grade Institution, ISO 9001:2015 Certified Institute, Recognized u/s 2(f) and 12(B) of the UGC Act 1956 Introduction to Data Science and Visualization Mrs. Kousar A. Nadaf Asst.professor,SITCOE,Yadrav
2. What is Data Science? •Interdisciplinary field •Combines statistics, computer science, and domain knowledge •Extracts insights from data “Data science is about turning raw data into meaningful knowledge.”
3. Importance of Data Science •Drives decision-making •Powers AI & machine learning •Helps businesses innovate
4. Data Science Workflow •Data Collection •Data Cleaning •Data Analysis •Modeling •Visualization & Communication
5. Tools in Data Science •Python, R •Jupyter Notebook •SQL •Tableau, Power BI “These tools help us process, analyze, and visualize data efficiently”
6. Introduction to Data Visualization •Graphical representation of data •Makes patterns visible •Simplifies complex information
7. Types of Visualizations •Bar chart •Line graph •Scatter plot •Heatmap
8. Principles of Good Visualization •Clarity •Accuracy •Simplicity “A good visualization is clear, truthful, and easy to interpret.”
9. Applications of Data Visualization •Business dashboards •Scientific research •Social media analytics •Healthcare monitoring
10. Conclusion •Data science = insights from data •Visualization = communication of insights •Together → better decisions
11. THANK YOU