Python for Data Science
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)
- Intermediate Python for Data Science
March 30, April 1, 7, 8, 2021: 8:45AM–12:15PM Details and Registration
- Advanced Python for Data Science
To be scheduled May/June 2021
PYTHON FOR DATA SCIENCE CERTIFICATE OF COMPETENCY (3 Classes)
- Introduction to Python for Data Science
- Intermediate Python for Data Science
- Advanced Python for Data Science or Fundamentals of Machine Learning
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
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.
| 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: $595
These trainings can also be customized and delivered at your location.
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.
| 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
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
