Muhammad Amil Busthon has completed
Introduction to Python for Data Science (Microsoft)
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Course Description
Labs for Introduction to Python for Data Science.
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.- 1
Hello Python
FreeLab Exercises on Hello Python.
- 2
Variables & Types
FreeLab exercises on Variables & Types.
- 3
Lists
FreeLab exercises on Lists.
- 4
Subsetting Lists
FreeLab exercises on Subsetting Lists.
- 5
List Manipulation
FreeLab exercises on List Manipulation.
- 6
Functions
FreeLab exercises on Functions.
- 7
Methods
FreeLab exercises on Methods.
- 8
Packages
FreeLab Exercises on Packages.
- 10
2D Numpy Arrays
FreeLab exercises on 2D Numpy Arrays.
- 11
Numpy Basic Statistics
FreeLab exercises on Numpy Basic Statistics.
- 12
Basic Plots with matplotlib
FreeLab exercises on Basic Plots with matplotlib.
- 13
Histograms.
FreeLab exercises on Histograms.
- 14
Customization
FreeLab exercises on Customization.
- 15
Boolean Logic & Control Flow
FreeLab exercises on Boolean Logic & Control Flow.
- 16
Pandas
FreeLab exercises on Pandas.
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.
Machine Learning Researcher
Filip is the passionate developer behind several of DataCamp's most popular Python, SQL, and R courses. He also led the development of DataLab, DataCamp's collaborative data science notebook. Holding degrees in Electrical Engineering and Artificial Intelligence, he currently works as a freelance machine learning researcher and data science educator.
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