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Coursera

Python and Statistics Foundations

Edureka via Coursera

Overview

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This course introduces Python programming and fundamental statistics concepts, equipping learners with essential skills for data-driven roles in tech and AI. Through hands-on experience, you'll learn how to manipulate data, visualize insights, and apply statistical techniques for data analysis. By the end of this course, you will be able to: - Understand and apply Python programming concepts such as data types, operators, and control structures - Manipulate data using popular libraries like NumPy and Pandas - Visualize data with Python libraries such as Matplotlib, Seaborn, and Plotly - Analyze data using statistical techniques, including measures of central tendency, dispersion, and probability - Perform hypothesis testing and draw insights from the data This course is designed for beginners, data enthusiasts, and aspiring data scientists who want to build a strong foundation in Python programming and statistical analysis. No prior programming experience is required, although familiarity with basic statistics will be helpful. Join us to start your journey into data analysis and programming with Python!

Syllabus

  • Python Essentials
    • Welcome to Python and Statistics Foundations, the first course in the AI Exploration program's series! This module is designed to help learners take a significant step towards launching their careers in tech. In the first week, we'll explore how Python programming concepts are essential for creating efficient programs. Let's get started!
  • Exploring Data with NumPy and Pandas
    • In the second week of this course, Learn how to manipulate data using NumPy and Pandas, working with various data formats. Gain proficiency in visualizing data using a range of charts and graphics.
  • Statistics in Python
    • In the third week of this course, we'll delve into statistics and probability. We'll explore measures of central tendency to handle various data inconsistencies. Additionally, we'll cover topics such as joint and marginal probability, as well as the fundamentals of hypothesis testing.
  • Course Wrap-up and Assessment
    • This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz on Python programming concepts, Data manipulation with NumPy and Pandas with Statistical Analysis

Taught by

Edureka

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