FRAMEWORK
ACADEMY
Courses
Log In
Join Free
Home
Courses
IT: Programming & Software Development
Foundations of Python Data Science
Curriculum
1 Section
28 Lessons
30 hours
Expand all sections
Collapse all sections
Unit 1 — Foundations of Python Data Science
28
1.1
Understanding Python as a Language
20 mins
1.2
Working with Python
20 mins
1.3
Working with Anaconda
20 mins
1.4
Defining Google Colab
20 mins
1.5
Using Jupyter Notebook
20 mins
1.6
Uploading, Streaming, and Sampling Data
20 mins
1.7
Juggling between NumPy and pandas
20 mins
1.8
Using the Bag of Words Model to Tokenize Data
20 mins
1.9
Contextualizing Problems and Data
20 mins
1.10
Starting with a Graph
20 mins
1.11
Choosing the Right Graph
20 mins
1.12
Playing with Scikit-learn
20 mins
1.13
The EDA Approach
20 mins
1.14
Understanding SVD
20 mins
1.15
Clustering with K-means
20 mins
1.16
Considering Outlier Detection
20 mins
1.17
Guessing the Number: Linear Regression
20 mins
1.18
Pondering the Problem of Fitting a Model
20 mins
1.19
Using Nonlinear Transformations
20 mins
1.20
Starting with a Plain Decision Tree
20 mins
1.21
Discovering the News with Reddit
20 mins
1.22
Removing Personally Identifiable Information
20 mins
1.23
Defining Data Science
20 mins
1.24
Performing Rapid Prototyping and Experimentation
20 mins
1.25
Installing Anaconda on Windows
20 mins
1.26
Working with Notebooks
20 mins
1.27
Performing Multimedia and Graphic Integration
20 mins
1.28
Accessing Data in Structured Flat-File Form
20 mins
This content is protected, please
login
and
enroll
in the course to view this content!
S
Ask SIERA
YOUR DIGITAL ASSISTANT
×
Modal title
Main Content