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Practicum is the best coding bootcamp 3 years in a row
graduates
find a tech job within 6 months
See what goes into these numbers in our
H2 2022 Graduate Outcomes Report
H2 2022 Graduate Outcomes Report
1k+
85%
You don’t need a tech background
All you need
is а love for
discovery
is а love for
discovery
Your new skillset
Matplotlib
Tableau
SQL
Pandas
Python
Machine Learning
A/B testing
Business Analytics
Pivot Tables
Scikit-learn
Google Sheets
Median>>graduate salary: $65,500
Learn in a work-simulated environment
Interactive platform
Enjoy a learning experience that's designed to engage. Learn concepts, practice coding, and receive feedback
in the same window.
Bite-sized interactive lessons are followed by coding practice, followed by projects that put it all together.
in the same window.
Bite-sized interactive lessons are followed by coding practice, followed by projects that put it all together.
Sprints
Week 1 — Theory + Practice
The learning process is divided into sprints—2-3 week planned periods of work towards a tangible outcome. Most tech companies work in sprints, so you'll show up prepared.
Each sprint caps off with a project that will be reviewed line-by-line by a data professional.
Each sprint caps off with a project that will be reviewed line-by-line by a data professional.
Week 2 — Work on project
Line-by-line code review
A professional data analyst will check every line of your code to make sure it works the way it's supposed to and follows industry best practices.
As a suggestion: instead of creating a variable raw and using row.iloc[O][-1], try to add column name to the first expression. Like df.loc[df.something == ‘smth’, ‘column_name’]
Mia Murray
Code reviewer
12 portfolio projects
Solve real-life business cases from day one.
Graduate with a double-digit portfolio demonstrating your applied skills in business analytics, product science, even machine learning.
Graduate with a double-digit portfolio demonstrating your applied skills in business analytics, product science, even machine learning.
Study is challenging but we’ll help you
Learning a new profession can feel daunting — that’s why we dedicate hours of support to help with your individual needs. We are here to cheer you on, provide advice, and help with coding tasks.
SQL
Business Analytics
Data Visualization
Python
Spreadsheets
Machine Learning
Don't give up! You’re surrounded
Community Managers
Guide you through the program
Code Reviewers
Give you feedback
Tech Support
Get your tools up and running
Career Coaches
Get you hired
Senior Students
Share experience and wisdom
Tutors
Teach you tech skills
Our job is to make sure you find a career you enjoy
Career Prep Course
Learn how to write a standout resume and cover letter, create a professional LinkedIn profile and GitHub portfolio, and rock your job search.
Free career coaching included
$4000 value
4+ free hours of mock interviews will give you the confidence to ace a real one
One-on-one sessions with a career coach to develop a job-search strategy.
Career coaching
Support beyond graduation
We'll stay in touch during your first two months of employment to make sure you're confident in your new position.
Externships
All students take on externships—real-life projects at actual companies. Boost your LinkedIn profile and impress your future employers with relevant projects and reviews from a real company.
EezyLife company's task: identify vegetarian restaurants from Yelp text reviews.
Approach: chose an explainable method like aspect-based sentiment analysis.
Approach: chose an explainable method like aspect-based sentiment analysis.
Permit company's task: develop targeted online ads based on the types of permits requested, by the types of users, in the most customer's areas.
Approach: create fully interactive dashboards and provide some insights.
Approach: create fully interactive dashboards and provide some insights.
Norbu company's task: to offer ideas how to increase app’s Retention Rate.
Approach: explore users' behavior, consider the nature of the stress, certain relief activities and alternatives used in the past.
Approach: explore users' behavior, consider the nature of the stress, certain relief activities and alternatives used in the past.
If you don’t get a job within six months of graduating Practicum, we will refund 100% of your tuition. Read more in our Terms of Use
Get paid or get a refund
Rated 4.8 out of 5
600+ reviews
600+ reviews
Former Legal Consultant
Blockchain Analyst at Nansen
Mega Septiandara
The real life projects are a great foundation to have upon graduation, I can already show off what I accomplished on Github.
Former Researcher
Data Analyst at Capgemini
Xia Cui
I enjoyed the course and every aspect of it: the platform, the tasks, the design, the flow, the support.
Former Petroleum engineer
ML engineer at Leidos
Chukwuemeka Okoli
My favorite part of the program is the project and code review. At the end when your project is approved, there is that satisfaction that comes from achieving a feat.
Worked in Digital marketing
Data Analyst at iPullRank
Atajan Abdyyev
I liked that there were real people and projects at Practicum, and that you had to finish projects in a certain amount of time.
Worked in Tourism Sales
Associate Data Scientist at Spotify
Rachelle Perez
Somehow I feel like we are part of a group trying to achieve something together despite working individually, helping each other when needed and celebrating each other’s win.
Worked in Engineering
Senior Data Analyst at Pendo.io
Jackie Lu
At Practicum I was glad to have resource to the career program, where students review each other’s resumes and provide moral support.
Program ._.structure
Program structure
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
6 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
Building an impactful analysis starts with understanding how to use SQL Databases to access and filter data. This module will explore industry best practices for choosing and calculating the right metrics and how to efficiently execute an analysis using spreadsheets.
Fundamentals of Business Analytics
4 weeks
80 hours
SQL
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
6 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
An analysis is only effective when you can clearly communicate it to your stakeholders. This module will focus both on how to build interactive data visualizations in Tableau and the best practices in developing persuasive stories for your presentations.
Data Visualization and Storytelling
4 weeks
80 hours
Tableau
Data analysis continues to become more sophisticated and some of the most advanced and powerful techniques utilize the Python programming language. This module is focused on building a solid foundation in Python and important software development tools used with Python.
Python Fundamentals
4 weeks
40 hours
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
6 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
Python
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
6 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
Learn to use powerful Python libraries for data analysis like Pandas for cleaning data and Matplotlib for visualizing data. Apply python to execute A/B tests and build dashboards for reporting.
Data Analysis with Python
6 weeks
120 hours
Matplotlib
Pandas
Learn how to apply Machine Learning (ML) algorithms to building predictive models. Using the scikit-learn Python library, you’ll learn how to train a ML model, measure it’s performance and implement the algorithm.
Intro to Data Science
4 weeks
80 hours
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
6 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
Scikit-learn
Program
Fundamentals of Business Analytics
5 weeks
Data Visualization and Storytelling
4 weeks
Python Fundamentals
4 weeks
Data Analysis with Python
4 weeks
Intro to Data Science
4 weeks
Applying Analytics for the Final Project
2 weeks
This module will focus on choosing the right combination of tools to accomplish a job. The final step in this course is a Final Project where students can demonstrate their mastery of data analytics.
Applying Analytics for the Final Project
2 weeks
80 hours
+
Externships: The Apiary
Externships: The Apiary
+
Career Prep Course
Career Prep Course
+
Career Acceleration
Career Acceleration
5–6 weeks
10–20 hours
up to 6 month