Data Scientist with Python Track

Gain the career-building Python skills need to succeed in data science, from data manipulation to machine learning:
  ✓ Learn to import, clean, manipulate, and visualize data.
  ✓ Get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, Scikit-learn and many more.
  ✓ Learn the statistical and machine learning techniques needed to perform hypothesis testing and build predictive models.

This track covers the following topics:

  1.   Introduction to Python
  2.   Intermediate Python
  3.   Data Manipulation with Pandas
  4.   Joining Data with Pandas
  5.   Introduction to Statistics in Python
  6.   Introduction to Data Visualization with Matplotlib
  7.   Introduction to Data Visualization with Seaborn
  8.   Introduction to Numpy
  9.   Python Data Science Toolbox1
10.   Python Data Science Toolbox2
11.   Intermediate Data Visualization with Seaborn
12.   Data Communication Concepts
13.   Introduction to Importing Data in Python
14.   Intermediate Importing Data in Python
15.   Cleaning Data in Python
16.   Working with Dates and Times in Python
17.   Writing Functions in Python
18.   Exploratory Data Analysis
19.   Analyzing Police Activity with Pandas
20.   Introduction to Regression with statsmodels in Python
21.   Sampling in Python
22.   Hypothesis Testing in Python
23.   Supervised Learning with scikit-learn
24.   Unsupervised Learning in Python
25.   Machine Learning with Tree-Based Models in Python

Click here to view the certificate

Additional Python courses:
    -   Web Scraping in Python
    -   Regular Expressions in Python
    -   Writing Efficient Python Code
    -   Writing Efficient Code with Pandas
    -   Statistical Thinking in Python (Part 1)
    -   Statistical Thinking in Python (Part 2)
    -   Case Study: School Budgeting with Machine Learning in Python
    -   Cluster Analysis in Python
    -   Dealing with Missing Data in Python
    -   Anomaly Detection in Python