Introduction to Python for Data Science

In this bootcamp, students will be learning core Python concepts and understand how to use the language as it relates to data science.

Course Description

Python has quickly become one of the most popular programming languages among individuals and organizations around the world. Its general purpose appeals to many different industries and allows professionals to transfer their skillset across careers, especially data science, machine learning, and artificial intelligence.

This Python bootcamp focuses specifically on data science. Throughout the course, you will practice the basics, learn more advanced techniques, and finish with a project to put all your newfound knowledge to use. In 5 days (5 – 6 hours per day) you can get started and polish your Python abilities for data science and analysis.

Fall Cohort starts Oct 19 – 23, 2020 @ 9 am – 12 noon PST

5 Days

5 – 6 hrs / day

Live instructor

Collaborative Remote Learning

Just like our live online data science certificate program, this python bootcamp is available wherever you prefer to learn. By using modern-day collaboration tools, students learn and chat with instructors and partners to work through real-world problems and understand outcomes. This is not a self-paced course. Every class is taught live and office hours are available daily for instructors and teaching assistants to answer all your questions.

What Will You Gain

Essential Python Skills

Python is the fastest growing programming language around the world. It is becoming an essential skill to have for a career in data science, ML or AI.

Real World Applications

Each practice exercise is created from a real-world point of view. Exercises in and outside of class are made to practice each concept/technique as you would use them on the job.

Python Certificate from UNM

After completing the Python for Data Science course, each new alumnus will receive a certificate of completion co-sponsored by the University of New Mexico.

Curriculum Timeline

Dealing with Data: Data Ingestion, Transformation, Cleaning, Exploration and Visualization

Data Loading, Storage and File Formats Day 1

This module will focus on building an understanding of how to Gather data from different sources. We will explore commonly used Python data structures such as data-frames and dictionaries and will learn about working with data from different data formats

Data Handling Techniques Day 1

In this module, we’ll be looking at Python’s powerful data handling techniques. You’ll be introduced to different methods that you will use to get the information you need from data stored in complex data structures.

Data Wrangling: Cleaning, Transforming, Merging and Reshaping Day 2

Once we’ve loaded our data into your Python environment, we’ll learn how to process it before it can be used for further analysis. This includes cleaning the data, reshaping it, merging data from multiple sources/data structures, and applying transformations.

Aggregation and Grouping Day 2

In this module, we learn about python’s powerful data aggregation and grouping techniques and how to use them to get useful insights from our data.

Data Exploration and Visualization Day 3

In this module, we will focus on understanding how to dissect and explore our data to uncover useful insights. We will also look at different visualization techniques to help present our data and findings and get acquainted with popular visualization packages in Python.

Real World Applications

Intro to Restful API Day 4

This module will be focused on the RESTful API, its functions and how it can be used to communicate with websites like Twitter and Reddit that have exposed endpoints to scrape data.

Data Pipelines in PythonDay 4

Once we’re comfortable with the RESTful API, we’ll look at how it can be used to get data from websites. We’ll use the data we scraped along with other data loading, parsing, cleaning and exploration techniques we learnt previously to build an end-to-end data pipeline.

Python Project Day 5

Coming soon