Data Analytics Bootcamp Online Part-Time

Data Analytics Bootcamp

Introduction

Career Support

Learning Process

Reviews

Tuition

Externships

Curriculum

FAQ

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Data Analytics Bootcamp

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7-month part-time online program for beginners

Data Analytics Bootcamp

7-month part-time online program for beginners

Learn more

Learn to process and communicate data >> strategically

Build a portfolio of 13+ completed >>> projects sourced from real business cases

Find a high-paying job with 50 hours of career>>>support

Receive a 100% refund >> if you’re not employed as a data professional within 6 months of graduation

You don’t need a tech background

All you need
is love for
discovery

Growth Analyst

Your future job title

Data and Insights Analyst

IT Analyst

Business Analyst

Data Analyst

Skillset you’ll get

Machine learning basics

Building dashboards

Results presentation

A/B testing

Business analytics

Statistical hypothesis testing

Matplotlib

Sci-kit learn

Pandas

Python

Plotly

Dash

Seaborn

Tableau

Average data analyst
cccsalary: $65,000

Book a call

Learn in a work-simulated environment

Interactive platform

Prepare for an engaging, capability-building experience. Our platform combines fundamental concepts, real-world data sets, and quizzes.

Experiment in our sandbox: Run any code, and don’t worry about making grave mistakes. In a sandbox, even the wildest experiments won’t cause any trouble.

Sprints

Week 1 — Theory + Practice

The learning process is divided into sprints, or two-to-three week long work intensive periods. Most tech companies work this way, so you will come prepared. Each sprint consists of interactive lessons and features a project with a deadline.

Week 2 — Work on project

Line-by-line code reviews

A professional data analyst will check each line of your code to make sure it works the way it's supposed to and conforms to 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

13 portfolio projects

From day one, you are going to solve real-life business cases. By the end of your program you’ll build a double-digit portfolio to demonstrate your applied skills in business analytics, product science, and 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 you with your specific needs. We are here to cheer you on, provide advice, and help with coding tasks.

SQL

Business Analytics

Data Preprocessing

Basic Python

Automation

Numerical Methods

Never give up! You’re surrounded

Community Managers

Make group learning fun

Code Reviewers

Give you feedback

Tech Support

Get all the software you may need up and running

Career Coaches

Get you employed

Senior Students

Provide you guidance

Tutors

Teach you skills

We don’t have

boring live lectures

hours-long videos

lesson plans from the 90s

a strict schedule

Our job is to make sure you find a career you enjoy

Career Prep Course

Learn how to write a standout resume and a cover letter, create LinkedIn and GitHub profiles, make a professional portfolio, and other employment pro-tips.

Free career coaching included

valued at $4000

4+ free hours of mock interviews will give you the confidence to nail a real one

One-to-one sessions with a career coach to develop a job-search strategy

Career coaching

Support beyond graduation

We stay in touch during the first two months of employment, to make sure you are confident in your new position.

Externships

All students will take on externships at actual companies with real life projects, we call them “Apiary projects”. 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.

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.

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.

Join Practicum open house webinar

Prepare for an engaging learning experience. Our platform combines theory, real scenario tasks, and quizzes all in one place.

How To Learn A New Profession With Practicum Bootcamps

Sign up for a webinar

Get paid or be refunded

If you don’t get a job within six months of graduating Practicum, we will refund 100% of your tuition.
Read more in Terms of Use

4.8 out of 5 rating based on 330+ reviews

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.

Rachelle Perez

Associate Data Scientist at Spotify

Worked in Tourism Sales

I liked that there were real people and projects at Practicum, and that you had to finish projects in a certain amount of time.

Atajan Abdyyev

Data Analyst, Digital marketing at Vizion Interactive

Worked in CS

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.

Chukwuemeka Okoli

ML engineer at Leidos

Former Petroleum engineer

It doesn’t matter how hard a subject is, I will always find help. The real life projects are also a great foundation to have upon graduation, I can already show off what I accomplished on Github.

It’s just awesome to see that twelve projects (guided) are also completed within the duration of the original program. In a nutshell, theories, tasks, projects, community and platform all contributed to make the program outstanding.

Saumik Barua

In my search for a comprehensive, intensive, yet practical learning environment to develop and consolidate my skills, I found Practicum. I picked Practicum based on reviews, and I'm extremely glad with this decision.

Xia Cui

Major advantage is how its tutors, project reviewers, and community managers deal with students' questions. First, they are professionals with real-world experience in the field, and, second and most important, all explanations or articles recommended by them are straight to the point and accurate.

Mabelly Tuchsznajder

Mega Septiandara

Data Analyst at Capgemini

Former Researcher

Read all reviews on Career Karma, Course Report and Switchup

Program structure

Download

Your introduction to the world of data science! Key concepts and basic syntax in Python. Loops, conditions, and functions. The pandas library for data analysis. Your first analytical case study, followed by your first project.

Compensating for less-than-perfect data. Handling missing and duplicate values. Changing data types. Systems thinking for analysts.

Performing initial scans to detect patterns in data. Building basic graphs and generating your first hypotheses.

Probability theory, the most common distributions, and statistical methods in Python. Sampling and statistical significance. Identifying and handling anomalies.

Identify patterns to help you determine whether a given video game will be commercially successful or not.

How databases are structured and how to pull data from them using SQL queries. Finding data online.

Applying data analysis in business. Business metrics and KPIs. User data analysis. Marketing analytics and related tools. The sales funnel.

Methods and tools for testing hypotheses. Experimental design. Seasonality. Cohort analysis. A/B testing.

Presenting your research. Data visualization  methods. Creating reports to explain findings. The seaborn library.

Bring together everything you’ve learned so far to analyze the results of a food app’s A/B test.

Automating data analysis processes and scripting routine tasks. Data visualization methods. Presenting results.

Machine learning methods and applications. Classification, forecasting, clustering. Regression. Decision trees.

Apply everything you've learned in a two-week program that recreates the experience of working as a junior analyst.

This is a course devoted to preparing for life after Practicum. During this course, you will learn how to create a resume, a LinkedIn profile, and a GitHub account, along with improving networking and interviewing skills. This course is self-paced and ends with a final task. We’ll also perform a review of your career artifacts.

Prepare for real-world interviews and gain experience through authentic practice. This program is designed to help you find a real job and also provides some work with technical skills.

Attend mock interviews
Receive 1:1 career coaching
Write technical articles and demonstrate your knowledge
Produce demo videos of your work
Participate in extracurricular activities
Join the Slack community

*Only available for students with permission to work in the US.

You'll gain confidence solving work tasks that use a real company's data to provide them with valuable insights. Learn to communicate with clients, meet their expectations, exchange peer reviews with colleagues, and present results to the company. The Apiary projects become available for participants sometime between the 8-10th Sprint, depending on the project. They are also available after graduation.

Assemble a portfolio project based on actual data
Get a recommendation on LinkedIn by a real company
Gain experience with freelance project workflow