Remote Live Instruction

Data Science Launchpad with Python

Develop a strong understanding of today’s most popular programming language by learning the widely adapted tools and methods for data analytics, data visualization, and machine learning in Python in 15 weeks.

Three Incredible Courses, One School Behind It All

Build your knowledge and gain confidence in transforming data sets into actionable insights with this data science program consisting of three courses delivered through remote live instruction.

Throughout the program, you will receive expert-led instruction and work on one hands-on lab and two data science projects to reinforce what you learned while being supported by a dedicated mentor. Upon successful completion of each course, you will earn a certificate that you can share with prospective employers and your professional network.

Program Overview

This bundle of three professional development courses starts by teaching students to write Python, which is readable, portable, and efficient. From there, students will learn the fundamental tools and methods for data analysis in Python and using these skills to distill business insights and communicate them through visualizations. Finally, students will build up their Machine Learning abilities in Python, being able to differentiate between several supervised and unsupervised models, and how to use those models to gain depth, discover structure, and create predictive tools based on observations.

Find out more information about our professional development courses.

Courses Included

  • Learn the basics of Python with a focus on Object-Oriented Programing
  • Gain comfort with basic data types and structures
  • Understand best practices and control flows
  • No previous coding background necessary
5 Seats Left
  • Dive deep into data analysis and visualization in Python
  • Wrangle datasets to discover insights
  • Use several contemporary packages for data analysis such as NumPy, SciPy, and pandas
  • Create visualizations using matplotlib and seaborn
  • Scrape the web with scrapy
5 Seats Left
  • Implement many commonly used machine learning models in Python
  • Learn the theory behind the various models
  • Train your models using sklearn, the quintessential machine learning module for Python
  • Apply the results of your models to gain depth in your understanding of the data
5 Seats Left
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Total: $4770.00
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Hands-on Lab work and Projects

Introductory Python

Data Cleaning and Object-Oriented Programming Lab

In the real world, a working data scientist may spend a lot of time cleaning and preparing messy data. In this directed lab, students will create their Python scripts and define Python objects while creating a tool to clean messy, real-world data. Students will bolster their skills by following best practices in the object-oriented programming paradigm and control flows of Python, and finish with their Python data cleaning tool.

Data Science with Python: Data Analysis and Visualization

Analytics and Visualization Project

This project aims to build on top of the new technical Python coding acumen and translate those techniques into part of a more extensive application toolbox learned by the students. The project allows students to experience working with an eye towards a use objective, with enough structure and direction that they gain skills that are transferable to a wide range of industries. Students will read in external data to the appropriate data structures, join multiple sources of data to find insights apparent only by considering the various sources simultaneously, create basic and easily interpretable statistical and visual descriptions of those insights. Furthermore, students will be encouraged to present their findings within a dash app.

Data Science with Python: Machine Learning

Insights through Machine Learning Project

This project aims to offer students a glimpse into using machine learning in the context of an insight-driven objective. Unlike many Kaggle-style machine learning projects, there will be an emphasis on the fact that the actual value of a model is not given by a single performance metric of that model. Successful completion will require the application of Data Analysis and Visualization with Python concepts within the context exploration, basic insights, and feature engineering. Students will also apply standard machine learning pipeline practices, including data preparation, model selection, and understanding and communicating the value the model provides within the domain context. Furthermore, students will learn to keep an eye towards the domain objective and how all parts communicate with this objective and play a supporting role in achieving it.

Demo Lecture

Hasan Aljabbouli
Instructor Hasan Aljabbouli walks through a lecture on Python string from the Introductory Python course.
Why Enroll in this Program?
Learn major tools and methods for data analytics and visualization
Acquire knowledge and skills in model design and selection for Machine Learning
Hands-on learning with two real-world data science projects
Understand additional advanced tools such as dash and Keras
Learn from home through remote live instruction
Gain guidance and support from expert instructor(s) and mentors

Tuition & Finance

Tuition Total
($400 saved)
Payment can be made either by credit card, PayPal, or through third-party financing for those who qualify.
Third-Party Financing Option Available
We work with our financing partner, Climb Credit, to offer loan options for eligible students. 95% of applicants will receive an instant decision after completing the quick 5-minute application from Climb Credit.

Preview your loan options and select the right financing solution for your educational investment. Visit Climb Credit to start your application.


Hasan Aljabbouli
Hasan Aljabbouli
Hasan Aljabbouli is an Assistant Professor in Computer Science. He obtained his Master's and Doctorate in Artificial Intelligence from Cardiff University in the United Kingdom and his Bachelor's in Engineering in Information Technology from Homs University. He worked for different universities and has published many scholastic materials in Data Mining and Machine Learning and its applications. In addition to his academic experience, Hasan received two patents and earned relevant experiences participating in various technical projects.

Student Testimonials

"I really enjoyed this class and after just one month I feel like I have strong foundation of Python. I had zero experience prior to taking the course. Classes were a combination of theory and practice."
Rafal Zabrinsky
Introductory Python graduate
"I highly recommend these classes to anyone who wants to take their analytics skills beyond Excel, Pivot Tables, and Averages, and into more advanced predictive modeling methods. Luckily, a lot of the work has already been done for us by the developers who created pandas, matplotlib, statsmodels, and scikit-learn. I didn’t know anything about these tools prior to taking this class."
Sam Brand
Data Science with Python: Machine Learning graduate

Start Learning Today

Enroll today and start gaining in-demand skills that can take you to the next level.

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