Foundational Python for Data Science
Python from the Ground Up
Notebook-based data science programming in Python is both popular and emerging, but also underserved for beginners. This training will provide a foundation of the Python language for the novice and beginner programmer who plans on contributing to the Data Science field. You’ll find the core parts of Python isolated for you to prepare for more specialization and training in the Data Science field. This course will give you just the python skills you’ll need for delving into and investigating data.
What you'll learn-and how you can apply it
- Use Google colab notebooks for Data Science Programming
- Use fundamental Python data structures such as lists, strings and dicts
- Learn how to manipulate data in Python using core python programming concepts
- Control execution with loops and conditionals
- Write and call functions
This training course is for you because...
- You are new to programming and wish to prepare for Data Science study.
- You work closely with Data Scientists in a Python shop and wish to better understand the language basics.
- You are a Product Manager, Data Analyst, or Marketeer who want to prepare to learn Data Science
- General computer skills are an asset, ex moving, copying, renaming, and deleting files on the computer they will be using
- Experience using text-editors and/or spreadsheet applications
- Comfort using web browsers and search engines
- A Google (gmail) account in order to access Google Colab
About your instructor
Kennedy Behrman is veteran consultant specializing in architecting and implementing cloud solutions for early stage startups. He has both undergraduate and graduate degrees from University of Pennsylvania, including a MS in Computer Information Technology and post-graduate work in the Computer Graphics and Game Programming program.
He is experienced in data engineering, data science, AWS solutions and engineering management, and has acted as a technical editor on a number of python and data science related publications. As a Data Scientist he helped develop a proprietary growth hacking machine learning algorithm for a startup that led to exponential growth of the platform. Afterwards, he then hired and managed a Data Science team that supported this technology. Additional to that experience, he has been active in the Python language for close to 15 years including giving talks at user groups, writing articles, and serving as technical editor to many publications.
The timeframes are only estimates and may vary according to how the class is progressing
Segment 1 Introduction to Colab and Python Fundamentals Length: 60 min - Instructors will introduce the use of Google Colab and introduce Python Fundamentals - Participants will follow along with their own Colab notebooks.
Q&A 10 min
Break 10 min
Segment 2 Data structures and execution control Length: 60 min - Instructors will introduce the most used Python built-in data structures and execution control statements - Participants will use lists, dictionaries, strings, for loops, while loops and if statements.
Q&A 10 min
Break 10 min
Segment 3 Functional programming and generators Length: 30 min - Instructors will briefly introduce principles of functional programming and generators - Participants will learn to use map, reduce, filter, list comprehensions, dict comprehensions, and generators
Q&A 10 min
Segment 4 Overview of major Data Science libraries Length: (30 min) - Instructors will give an overview of the major third-party libraries used in the practice of Data Science