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Data Science

Python for Data Science

Group Training + View more dates & times

Developers Use Python

41.7% of Developers Use Python

Developers Love Using Python

73.1% of Developers Love Using Python

Python is the fastest growing major programming language today

Fastest Growing Language Today!

This course introduces the Python language to students who want to use Python as a tool for their data science initiatives. The goal is to become proficient enough with the Python language to leverage powerful Data Science packages such as Pandas and matplotlib.

This is a comprehensive introduction to Python programming with a focus on understanding and using the Pandas library for storing data in DataFrames and plotting portions of the data with matplotlib. In addition to data visualization, you will learn how to use the Pandas library to import and filter data. Typical data science skills such as data interpretation and analysis will be addressed.

“I really liked Jason and thought he was an effective instructor. He was able to hold my attention for most of the time which is a challenge for all-day classes. Probably the best instructor I’ve had in several years. Would recommend it to others who are new to Python and data science. Thought the online delivery worked great.” 

John P.
Python For Data Science Student

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Who Should Take This Course


This course is suitable for:

  • Data analysts,
  • Data scientists,
  • Data engineers,
  • Developers



Students should have a basic proficiency in some programming language. Prerequisite language skills include understanding of datatypes, Boolean logic, control flow and basics of collections, such as arrays or hash tables. An understanding of using Excel for data manipulation is helpful.


Python for Data Science Training Course Sample Content

Still Not Sure This Is The Course For You?

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Course Outline

Python Data Science Ecosystems

  • Connecting to Jupyter Notebooks
  • Data Science Overview Example
  • Python from the Command Line
  • Exporting a Simple Notebook


Jupyter Notebook Basics

  • Cell Types
  • Edit and Command Mode
  • Running cells
  • Output
  • Restarting the Kernel
  • Exporting the Notebook
  • Cell and Line Magics


Python Basics

  • Comments, Indenting, print()
  • Variables
  • Types
  • Operators
  • Control Flow



  • Lists
  • Tuples
  • Sets
  • Dictionaries



  • Built-in Functions
  • User-defined functions
  • Anonymous in-line functions


Using Modules

  • Importing and Selective Importing
  • Properties
  • Methods


Data Sources and Formats

  • CSV, TSV
  • JSON
  • SQL


Using NumPy

  • ndarray
  • Indexing and Slicing
  • Sorting


Pandas Basics

  • Why Pandas?
  • Series
  • DataFrames
  • Populating DataFrames
  • Importing CSV, Excel, SQL Data
  • DataFrame Columns and Cells
  • DataFrame Retrieval


Pandas and Data Analysis

  • Functions on DataFrames
  • Mapping
  • Using Lambdas
  • Sorting
  • Statistics
  • Merging and Concatenating DataFrames
  • Data Cleaning
  • Data Analysis
  • Groupby
  • Aggregate Functions


Data Visualization

  • Plotting with matplotlib
  • Enhancing Visualizations with seaborn
Is there a discount available for current students?

UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.

What is the cancellation and refund policy?

Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.

Do you offer group training for the Python for Data Science course?

Yes! We offer private training for groups of 8 or more students. Submit the form below to request more information about setting up a private class.

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