Python for Data Science

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Python is one of the most powerful and widely used programming languages available. Its easily understood syntax makes it a popular choice for new coders, while its library or open source modules for everything from web development to data analysis make it the tool of choice for many data scientists.  These courses will familiarize students with the use of Python for data science and the common libraries to perform typical data science operations.

   
  • Introduction to Python for Data Science (no prior experience required)
          Nov 3, 5, 10, 12:   8:45AM–12:15PM-Register at  https://cvent.me/gZbadV
  • Intermediate Python for Data Science
     
          Jan 12, 14, 19, 21:  8:45AM–12:15PM-Register at https://cvent.me/yREWkr
  • Advanced Python for Data Science

 


PYTHON FOR DATA SCIENCE CERTIFICATE OF COMPETENCY (3 Classes)

To achieve a Certificate of Competency, all classes must be taken through the Center for Business Analytics.  In the event that professional experience meets the prerequisite for a class, another approved class may be substituted (limited to 1 class per Certificate of Competency)


Introduction to Python for Data Science

Next Class:  Nov 3, 5, 10, 12:   8:45AM–12:15PM

This course is designed to be an introduction to Python and its uses as a data analytics tool. The material will emphasize the core concepts in Python, specifically data types, data structures, functions, and classes and how they can be implemented and used to address data analytics problems. Popular modules used in data analysis will also be covered at a high level to include both NumPy, Matplotlib, and statsmodels.

                               Introduction to Python for Data Science Course Outline
Day One Day Two  
Introduction
Python and Jupyter Overview
Fundamentals
Packages, Modules, Methods, Functions
Importing Data
Selecting snd Filtering Data
Working with Columns
Case study: Part 1Q & A
 
Case study: Part 1review
Summarizing Data
Summarizing Grouped Data
Joining Data
Exporting Data
Visualizing Data
Case study: Part 2
Case study: Part 2 review
Q & A

 

4 online sessions

Online Course Fees: $495   

These trainings can also be customized and delivered at your location.


Intermediate Python for Data Science

Next Class: Jan 12, 14, 19, 21:  8:45AM–12:15PM

This short course provides a more detailed information on how programming with Python can make working with data easier and a deeper dive into data visualization. You will learn how to program more efficient data science applications in Python using control flow and custom functions, gain comfort with Python on the command line, be exposed to modeling with the scikit learn package and a few of the leading data visualization packages of Python.

PREREQUISITE: Attendance at the Introduction to Python for Data Science training or previous experience using Python for data analysis in a professional environment.

                                      Intermediate Python for Data Science Course Outline.
Day One Day Two  
Introduction
Working with data using pandas
Conditions
Iterations
Functions
Applying functions to pandas dataframes
Case study: Part 1Q & A
Case Study Part 1 Review
Python from the shell
Kernels and environments
Python data science ecosystem
Modeling with sci-kit learn
Case study: Part 2
Case study: Part 2 reviewQ & A
 
 

4 online sessions

Online Course Fees: $595  

These trainings can also be customized and delivered at your location.


Advanced Python for Data Science

This is a two-day course that introduces how one can use Python for advanced data science tasks, such as deep learning and natural language processing. Most of the time will be spent working through example problems end-to-end in the classroom. Students will learn the fundamentals of the Keras package (for deep learning) and will explore several NLP packages and methodologies to see the strengths of each. Some additional time will be reserved for discussion of real programming challenges students have encountered, and for an overview of related relevant technologies students may need in an industry setting (e.g. Git and GitHub).

Objectives

  • Develop an intuition for what problems are suited to deep learning- and/or NLP-based solutions.
  • Build familiarity with the basic interfaces of key Python libraries for deep learning and NLP: Keras, FuzzyWuzzy, and gensim.
  • Gain a high-level understanding of the function of data science-adjacent technologies that students will encounter in the workplace, focusing on Git and GitHub.

Prerequisites: Attendance at Introduction and Intermediate Python for Data Science classes or the following experience and skills.

  • Strong understanding of core Python concepts: variables, loops, conditionals, and functions
  • Some experience using Jupyter Notebooks or Jupyter Lab
  • Solid grasp of Pandas and how to use it for data manipulation: filtering, selecting, aggregating, slicing (indexing), and updating
  • High-level understanding of modeling concepts: training and test data, model accuracy, and overfitting

Python for Data Science Instructors

Photo of Ethan Swan Python Instructor

Ethan Swan is a senior data scientist at 84.51°, where he has been teaching Python and Linux courses since 2016. He holds a BS in computer science and an MBA from the University of Notre Dame. In his free time, he enjoys working on technology projects and is a contributor to the NBA API package on PyPI.

Website: ethanswan.com

Twitter: @eswan18

Instructor: Brad Boehmke, PhD, is the Director of Data Science at 84.51°, Professor at three universities, author of the Data Wrangling with R book, and creator of multiple R open source packages and data science short courses. He focuses on developing algorithmic processes, solutions, and tools that enable 84.51° and its analysts to efficiently extract insights from data and provide solution alternatives to decision-makers. He has a wide analytic skill set covering descriptive, predictive, and prescriptive analytic capabilities applied across multiple domains including retail, healthcare, cyber intelligence, finance, Department of Defense, and aerospace. Summary of his works is available online at bradleyboehmke.github.io.


Online Course Fee: $595  

 

These and other training can also be customized and delivered at your location


For more information about these classes, or for custom training classes, please contact
Headshot of Larry Porter

Larry Porter

Training, Marketing and Sponsorship

513-556-4742