Introduction to Data Science in Python

This course is part of Applied Data Science with Python Specialization

Instructor: Christopher Brooks

What you'll learn

  •   Understand techniques such as lambdas and manipulating csv files
  •   Describe common Python functionality and features used for data science
  •   Query DataFrame structures for cleaning and processing
  •   Explain distributions, sampling, and t-tests

    • Skills you'll gain

  •   Probability & Statistics
  •   NumPy
  •   Python Programming
  •   Data Science
  •   Data Manipulation
  •   Data Import/Export
  •   Pivot Tables And Charts
  •   Data Cleansing
  •   Statistical Analysis
  •   Pandas (Python Package)
  •   Data Structures
  •   Data Analysis
  •   Jupyter
  •   Programming Principles

    • There are 4 modules in this course

    This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.

    Basic Data Processing with Pandas

    More Data Processing with Pandas

    Answering Questions with Messy Data

    Explore more from Data Analysis

    Python Fundamentals and Data Science Essentials

    Python for Data Science

    Python for Data Analytics

    Data Analysis Using Python

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