Want to learn data analytics in 2024? This is the internet’s best curriculum.
Curated by David Venturi for the Data Maverick community
In this article, I outline the 90 hours of the internet’s best data analytics courses, articles, and projects in my Data Maverick: Data Analyst Bootcamp. Plus, how much it costs, and how to sign up and start learning.
If you want to become a data analyst the fastest, most efficient, and most affordable way possible in 2024, this is the program for you.
Join our private Discord community to get:
- access to the curriculum in checklist format,
- scheduled 90-day cohorts where you have access to private coaches and build genuine friendships for guidance and accountability,
- and more.
Why you should trust my picks
My name is David, and I created this curriculum-based community for my former self.
Back in 2015, I dropped out of school to create my own data science curriculum. I bet on two things:
- The courses on global EdTech platforms could be cobbled together to create a program better than the one at my local university.
- Blogging about what I learned via the projects I created could effectively replace my university’s “trusted” credential and a GPA.
I learned more efficiently, saved $30,000+, and gained freedom of location and schedule. The bet struck a note with many and an improved version of my curriculum went viral in 2017. That internet fame caught the interest of industry-leading EdTech companies, and over the next few years, I shaped curricula and taught courses for them.
Since then, I’ve received many messages asking what my latest recommendations for learning skills are, but with the full-time gig I did not have the bandwidth to answer in detail.
I do now. My Data Maverick program is my original curriculum, but:
- niched down to data analytics (my expertise)
- smarter (I’ve learned a lot since 2017)
- with new content from expert instructors (the data education industry has proliferated)
- with better learning tools (AI-assisted software wins),
- and with a gamified community (the final piece — incentivize and foster progress).
The future of education is already here, and this my implementation of it.
Schedule
This curriculum is 90 hours total. It can be self-paced or completed with a cohort in our community.
We have cohorts starting every second month with optional 3-hour coach-led group study sessions scheduled every Monday, Wednesday, and Friday. Our community members have tried more hours per week and more days per week, but 3 sessions with 3-hour study is the sweet spot. Ambitious, yet sustainable.
At this pace, most of our members complete the program in 90 days.
Cost
The prices of some of my recommended courses vary depending on your billing location and how long you take to complete them. Full-time learners in the United States will spend $117 on the courses below (three months of a DataCamp subscription). You can also spend a bit more to get an annual subscription — most of our community members do this.
I’ve selected data analyst-related articles by Cassie Kozyrkov (Google’s Chief Decision Scientist) and featured them throughout the curriculum. These articles are free.
Let’s begin.
Note: Data Maverick HQ is learner-supported. Some of the links provided below are affiliate links, which means that I will receive a commission (at no extra cost to you) if you use that link to make a purchase.
There are three sections in the curriculum: Programming for Data Analytics, Data Analysis in Python, and Data Analysis in SQL. At the end, there is a Certification section where you will complete DataCamp’s Professional Data Analyst Certification.
Programming for Data Analytics
Total time: ~10 hours
- Welcome to Data Maverick HQ. An orientation message by me. 5 minutes. Join our community for access.
- Thinking of Becoming a Data Analyst? You’re One Already! A Medium article by Cassie Kozyrkov. 5 minutes. Free.
- Chapter 1 of Python for Everybody. A course by Dr. Charles Severance hosted (with his permission) in our Data Maverick HQ Discord. 1 hour. You can also take the course on Coursera and get a Coursera certificate. I only include Chapter 1 of this course because I like how he answers the question, “Why Program?” with narrated videos of how the insides of computers work. To learn to code in Python, I prefer this next course.
- Introduction to Python. A course by Hugo Bowne-Anderson on DataCamp. Sign up for a DataCamp subscription for access to DataCamp’s entire catalogue, which you’ll use throughout this curriculum. 4 hours.
As you’ll notice throughout the rest of the curriculum, I favor DataCamp courses. I wrote a full explanation why in this article. The short version is:
I want short videos with automatic grading that delivers targeted feedback when students make a mistake. The goal here [is] to gauge for and maximize completion rate and learning outcome achievement.
DataCamp courses are four hours long and have 3–4 minute videos, then interactive exercises to test and grade video content. Beyond that, they also use a proprietary automatic grading system that points out learner mistakes and guides them to the correct solution. The result is DataCamp courses have completion rates significantly higher than the industry average (60% vs. 15%). I therefore default to DataCamp courses when evaluating a subject area within data science.
I’ve coached students through Python for Everybody (the course above I only recommend to take Chapter 1 from) and they often get stuck and frustrated with ambiguous feedback from that course’s autograder. DataCamp’s autograder does not have this problem, and the instructor and videos are also of high quality so I recommend their introduction to programming courses instead to save you time and frustration. The 2,500+ companies and 80% of the Fortune 1000 that use DataCamp to upskill their teams have likely identified this same value. Let’s continue with the curriculum.
- Intermediate Python. A course by Hugo Bowne-Anderson on DataCamp. 4 hours.
- Introduction to ChatGPT. A course by James Chapman on DataCamp. 1 hour.
- Becoming a “real” data analyst. A Medium article by Cassie Kozyrkov. 7 minutes. Free.
Data Analysis in Python
Total time: ~40 hours
- Understanding Data Science. A course by Lis Sulmont, Sara Billen, and Hadrien Lacroix on DataCamp. 4 hours.
- Data Manipulation with pandas. A course by Richie Cotton and Maggie Matsui on DataCamp. 4 hours.
- Joining Data with pandas. A course by Aaren Stubberfield on DataCamp. 4 hours.
- Introduction to Statistics in Python. A course by Maggie Matsui on DataCamp. 4 hours.
- Introduction to Data Visualization with Seaborn. A course by Erin Case on DataCamp. 4 hours.
- Data Manipulation with Python. A DataCamp skill assessment. 10 minutes.
- Importing & Cleaning Data with Python. A DataCamp skill assessment. 10 minutes.
- Exploratory Data Analysis in Python. A course by Izzy Weber and George Boorman on DataCamp. 4 hours.
- What’s the difference between analytics and statistics? A Medium article by Cassie Kozyrkov. 6 minutes. Free.
- Shifting your mindset from amateur to professional analyst. A Medium article by Cassie Kozyrkov. 8 minutes. Free.
- How to form realistic expectations about data. A Medium article by Cassie Kozyrkov. 6 minutes. Free.
- Sampling in Python. A course by James Chapman on DataCamp. 4 hours.
- Hypothesis Testing in Python. A course by James Chapman on DataCamp. 4 hours.
- Statistics for people in a hurry. A Medium article by Cassie Kozyrkov. 8 minutes. Free.
- How to spot a data charlatan. A Medium article by Cassie Kozyrkov. 9 minutes. Free.
- How to Add Value as a Data Analyst. A Medium article by Cassie Kozyrkov. 7 minutes. Free.
- Project: Data Analysis in Python. Your second project. Instructions provided in our community. 5 hours.
Data Analysis in SQL
Total time: ~40 hours
- Introduction to SQL. A course by Izzy Weber on DataCamp. 2 hours.
- Intermediate SQL. A course by Jasmin Ludolf on DataCamp. 4 hours.
- Joining Data in SQL. A course by Maham Khan on DataCamp. 4 hours.
- Data Manipulation in SQL. A course by Mona Khalil on DataCamp. 4 hours.
- PostgreSQL Summary Stats and Window Functions. A course by Michel Semaan, and Fernando Gonzalez Prada on DataCamp. 4 hours.
- Functions for Manipulating Data in PostgreSQL. A course by Brian Piccolo on DataCamp. 4 hours.
- Exploratory Data Analysis in SQL. A course by Christina Maimone on DataCamp. 4 hours.
- Data-Driven Decision Making in SQL. A course by Irene Ortner, Tim Verdonck, and Bart Baesens on DataCamp. 4 hours.
- Understanding Data Visualization. A course by Richie Cotton on DataCamp. 2 hours.
- How expert analysts think about time. A Medium article by Cassie Kozyrkov. 4 minutes. Free.
- Analytical Excellence Is All about Speed. A Medium article by Cassie Kozyrkov. 6 minutes. Free.
- Project: Data Analysis in SQL. Instructions provided in our community. 5 hours.
Certification
- 10 Differences Between Amateurs and Professional Analysts. A Medium article by Cassie Kozyrkov. 8 minutes. Free.
- DataCamp Professional Data Analyst Certification. A certification on DataCamp. Outside of the time calculation for our curriculum.
And that’s my take on the internet’s best curriculum for aspiring analytics pros in 2023. I invite you to join our community to begin forging your journey to data analyst financial freedom.
