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Home > Training > Big Data > Learn Data Science, Statistics, and Machine Learning using Python Training

Learn Data Science, Statistics, and Machine Learning using Python Training

Course#: TP2604

Designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science, this course’s content can be adjusted based on student experience level with Python to include full overview of Python and programming if necessary. The course can be adjusted to be between 3-5 days, depending on desired student outcomes and student experience.


  • Learn how to program with Python
  • How to create amazing data visualizations
  • How to use Machine Learning with Python


  • Programming with Python
  • NumPy with Python
  • Use matplotlib and Seaborn for data visualizations
  • Web scraping with Python
  • Using pandas Data Frames to solve complex tasks
  • Use pandas to handle Excel Files
  • Connect Python to SQL
  • Use plotly for interactive visualizations
  • Machine Learning with SciKit Learn
  • and much more!

Each section of the course consists of several lectures and ends with a full project exercise.
Each Machine Learning Topic has a full walkthrough project and a full exercise to test comprehension.

Skills Gained

By the end of this course training students will be able to:

  • Comfortably program with Python
  • Use Python and pandas to read data from a variety of sources (SQL, Excel, CSV, HDFS, etc)
  • Use multiple libraries to create data visualizations
  • Use Python's SciKit Learn library to implement Machine Learning Models
  • Understand how to use Spark to deal with big data and distributed systems


Students should have some programming experience in a programming language.


4 Days

Outline of TP2604 Learn Data Science, Statistics, and Machine Learning using Python Training

1. Python Basics Overview


2. Python for Statistics


3. Python for Data Analysis - NumPy


4. Python for Data Analysis - pandas


5. Python for Data Analysis - pandas Exercises


6. Python for Data Visualization - matplotlib


7. Python for Data Visualization - Seaborn


8. Python for Data Visualization - pandas Built-in Visualization


9. Python for Data Visualization - Plotly and Cufflinks


10. Python for Data Visualization - Geographical Plotting


11. Data Capstone Projects


12. Introduction to Machine Learning


13. Linear Regression


14. Cross Validation and Bias Variance Trade-Off


15. Logistic Regression


16. K Nearest Neighbors


17. Decision Trees and Random Forests


18. Support Vector Machines


19. Recommender Systems


20. K Means Clustering


21. Principal Component Analysis


22. Natural Language Processing


23. Hadoop and MapReduce Overview


24. Spark Overview


25. PySpark Overview


26. PySpark Exercises


27. Introduction to MLlib with Spark

We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston, Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.
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