Introduction to Data Science

A high-level overview of key Data Science disciplines is provided in this course. Along with an overview of frequent advantages, difficulties, and adoption problems, a fundamental grasp of data science from both a commercial and technological standpoint is given.

 

You will master the fundamentals of data science in this course, as well as how to use Python, a potent open-source tool. You will learn about fascinating ideas including exploratory data analysis, basic statistics, testing of hypotheses, tools for regression and classification modeling, and an introduction to machine learning.

 

  • Data Science Tools & Technologies
  • Statistics for Data Science
  • Python for Data Science
  • Exploratory Data Analysis
  • Advanced Statistics & Predictive Modeling
  • Optimize Model Performance
  • Dimensionality Reduction
  • Basics of Machine Learning

 

  • A beginner who is interested in data science and want to learn basic data science skills
  • Those looking for a more robust, structured data science learning program
  • Data Analysts, Economists, or Researchers
  • Software or Data Engineers

 

  • Introduction to Data Science
  • Analytics Landscape
  • Life Cycle of a Data Science Projects
  • Data Science Tools & Technologies
  • Measures of Central Tendency
  • Measures of Dispersion
  • Descriptive Statistics
  • Probability Basics
  • Marginal Probability
  • Bayes Theorem
  • Probability Distributions
  • Hypothesis Testing

  • Install Anacond
  • Data Types & Variables
  • String & Regular Expressions
  • Python list
  • Python dictionaries
  • Python set
  • Python tuple
  • Comprehensions

 

  • For Loop
  • While Loop
  • Break Statement
  • Next Statements
  • Repeat Statement
  • if, if…else Statements
  • Switch Statement
  • Writing your own functions (UDF)
  • Calling Python Functions

 

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