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Course Content
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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