Data Science
Python for Data Science
41.7% of Developers Use Python
73.1% of Developers Love Using Python
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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Audience
This course is suitable for:
- Data analysts,
- Data scientists,
- Data engineers,
- Developers
PREREQUISITES
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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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
Collections
- Lists
- Tuples
- Sets
- Dictionaries
Functions
- 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.