Interactive Course

Introduction to Python for Data Science (Microsoft)

  • 0 hours
  • 0 Videos
  • 75 Exercises
  • 73,888 Participants
  • 6,750 XP

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Course Description

Labs for Introduction to Python for Data Science.

  1. 1

    Hello Python

    Lab Exercises on Hello Python.

  2. 3

    Lists

    Lab exercises on Lists.

  3. 5

    List Manipulation

    Lab exercises on List Manipulation.

  4. 7

    Methods

    Lab exercises on Methods.

  5. 9

    Numpy

    Lab exercises on Numpy.

  6. 11

    Numpy Basic Statistics

    Lab exercises on Numpy Basic Statistics.

  7. 13

    Histograms.

    Lab exercises on Histograms.

  8. 15

    Boolean Logic & Control Flow

    Lab exercises on Boolean Logic & Control Flow.

  9. 2

    Variables & Types

    Lab exercises on Variables & Types.

  10. 4

    Subsetting Lists

    Lab exercises on Subsetting Lists.

  11. 6

    Functions

    Lab exercises on Functions.

  12. 8

    Packages

    Lab Exercises on Packages.

  13. 10

    2D Numpy Arrays

    Lab exercises on 2D Numpy Arrays.

  14. 12

    Basic Plots with matplotlib

    Lab exercises on Basic Plots with matplotlib.

  15. 14

    Customization

    Lab exercises on Customization.

  16. 16

    Pandas

    Lab exercises on Pandas.

  1. 1

    Hello Python

    Lab Exercises on Hello Python.

  2. 2

    Variables & Types

    Lab exercises on Variables & Types.

  3. 3

    Lists

    Lab exercises on Lists.

  4. 4

    Subsetting Lists

    Lab exercises on Subsetting Lists.

  5. 5

    List Manipulation

    Lab exercises on List Manipulation.

  6. 6

    Functions

    Lab exercises on Functions.

  7. 7

    Methods

    Lab exercises on Methods.

  8. 8

    Packages

    Lab Exercises on Packages.

  9. 9

    Numpy

    Lab exercises on Numpy.

  10. 10

    2D Numpy Arrays

    Lab exercises on 2D Numpy Arrays.

  11. 11

    Numpy Basic Statistics

    Lab exercises on Numpy Basic Statistics.

  12. 12

    Basic Plots with matplotlib

    Lab exercises on Basic Plots with matplotlib.

  13. 13

    Histograms.

    Lab exercises on Histograms.

  14. 14

    Customization

    Lab exercises on Customization.

  15. 15

    Boolean Logic & Control Flow

    Lab exercises on Boolean Logic & Control Flow.

  16. 16

    Pandas

    Lab exercises on Pandas.

What do other learners have to say?

Devon

“I've used other sites, but DataCamp's been the one that I've stuck with.”

Devon Edwards Joseph

Lloyd's Banking Group

Louis

“DataCamp is the top resource I recommend for learning data science.”

Louis Maiden

Harvard Business School

Ronbowers

“DataCamp is by far my favorite website to learn from.”

Ronald Bowers

Decision Science Analytics @ USAA

Filip Schouwenaars
Filip Schouwenaars

Data Science Instructor at DataCamp

Filip is the passionate developer behind several of DataCamp's interactive courses, covering both R and Python. Under the motto 'Eat your own dog food', he has used the techniques DataCamp teaches its students to perform data analysis for DataCamp. Filip holds degrees in Electrical Engineering and Artificial Intelligence.

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