Introduction to Data Science
High-Format Presentation
What is Data Science?
• Data Science is a multidisciplinary field that
uses scientific methods, algorithms, and
systems to extract knowledge and insights
from structured and unstructured data.
Evolution of Data Science
• - Early Data Analysis: Manual computation and
statistics
• - Business Intelligence: Automated data
processing
• - Modern Data Science: Machine learning and
big data technologies
Components of Data Science
• - Data Collection and Engineering
• - Exploratory Data Analysis
• - Machine Learning & Statistical Modeling
• - Data Visualization and Communication
Skills Required for Data Scientists
• - Programming (Python, R)
• - Data Wrangling and Cleaning
• - Statistical Analysis and Modeling
• - Communication and Visualization Skills
• - Domain Knowledge
Popular Tools in Data Science
• - Python & R
• - Jupyter Notebook
• - TensorFlow & Scikit-learn
• - Apache Spark
• - Tableau & Power BI
Industries Using Data Science
• - E-commerce and Retail
• - Healthcare and Pharmaceuticals
• - Banking and Finance
• - Manufacturing and Logistics
• - Government and Public Sector

Introduction_to_Data_Science_PPT2.pptx format

  • 1.
    Introduction to DataScience High-Format Presentation
  • 2.
    What is DataScience? • Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
  • 3.
    Evolution of DataScience • - Early Data Analysis: Manual computation and statistics • - Business Intelligence: Automated data processing • - Modern Data Science: Machine learning and big data technologies
  • 4.
    Components of DataScience • - Data Collection and Engineering • - Exploratory Data Analysis • - Machine Learning & Statistical Modeling • - Data Visualization and Communication
  • 5.
    Skills Required forData Scientists • - Programming (Python, R) • - Data Wrangling and Cleaning • - Statistical Analysis and Modeling • - Communication and Visualization Skills • - Domain Knowledge
  • 6.
    Popular Tools inData Science • - Python & R • - Jupyter Notebook • - TensorFlow & Scikit-learn • - Apache Spark • - Tableau & Power BI
  • 7.
    Industries Using DataScience • - E-commerce and Retail • - Healthcare and Pharmaceuticals • - Banking and Finance • - Manufacturing and Logistics • - Government and Public Sector