Want to learn data analytics in 2023? This is the internet’s best curriculum.
Curated by David Venturi for the Data Maverick community
In this article, I outline the 27 days of the internet’s best data analytics courses, articles, and projects in my Data Maverick: Initiation program. 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 2023, this is the program for you.
Join our free private Discord community to get:
- access to the entire curriculum (there are 2 key resources in this article exclusively for members)
- camaraderie and support to keep you on track in your learning journey.
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 programs are my original curriculum, but:
- 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 progress).
The future of education is already here, and this my implementation of it.
Schedule
This curriculum is self-paced, so you can complete the curriculum on your own schedule despite the 27 days of content listed below. Each day is roughly 4 hours, which I’ve found to be the maximum amount of time one can sustainably learn in a day in my time learning online. 27 days x 4 hours = 108 hours total.
Most learners finish the curriculum in less than two months so we have cohorts starting every Monday in our private Discord community so you can progress through the content with other folks at the same time.
Cost
The prices of my recommended courses vary depending on your billing location. For folks in the United States, the courses below cost $88 (one month of a Coursera Specialization subscription and one month of a DataCamp subscription).
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 is learner-supported. Some of the links to the resources in this guide are affiliate links, meaning I receive a commission (at no extra cost to you) if you use that link to make a purchase.
Python Programming
Day 1
- Welcome to Data Maverick. An orientation email by David Venturi. 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 Programming for Everybody (Getting Started with Python). 4 hours. Part of a Specialization by Dr. Charles Severance on Coursera. Sign up for a Python for Everybody Specialization subscription for access to this entire course, as well as the next course on Day 12. For more details on why I picked this course, check out this article:
Day 2
- Chapter 2 of Programming for Everybody (Getting Started with Python). 4 hours.
Day 3
- Chapters 3 & 4 of Programming for Everybody (Getting Started with Python). 5 hours.
Day 4
- Chapter 5 of Programming for Everybody (Getting Started with Python). 3 hours.
Day 5
- Chapter 6 of Python Data Structures. 4 hours. Part of a Specialization by Dr. Charles Severance on Coursera. Continue using your Python for Everybody Specialization subscription for access to the entire course.
Day 6
- Chapter 7 of Python Data Structures. 3 hours.
Day 7
- Chapter 8 of Python Data Structures. 3 hours.
Day 8
- Chapter 9 & 10 of Python Data Structures. 5 hours.
Day 9
- Introduction to Data Science in Python. A course by Hillary Green-Lerman on DataCamp. Sign up for a DataCamp subscription for access to DataCamp’s entire catalogue, which you’ll use throughout this curriculum. 4 hours.
Day 10
- Becoming a “real” data analyst. A Medium article by Cassie Kozyrkov. 7 minutes. Free.
- Python Programming. A DataCamp skill assessment. 10 minutes.
- How to Create Engaging Data Analysis Projects. A livestream with Q&A with me (David Venturi) in the Data Maverick Discord community. 1 hour. Join our community for access.
- Start Project: Python Programming. Your second project. Completed on DataCamp Workspace using the livestream from Day 3 as a guide. 4 hours.
Day 11
- Finish Project: Python Programming. 4 more hours.
Day 12
- How to Create a Data Analyst Portfolio That Gets You Noticed. A PDF by David Venturi. 10 minutes. Join our community for access.
- Project: Start Building Your Online Presence. Completed using the PDF above as a guide. 24 minutes.
Exploratory Data Analysis
Day 13
- Chapters 1, 2 & 4 of Streamlined Data Ingestion with pandas. A course by Amany Mahfouz on DataCamp. 3 hours.
Day 14
- Web Scraping in Python. A course by Thomas Laetsch on DataCamp. 4 hours.
Day 15
- Data Manipulation with pandas. A course by Richie Cotton and Maggie Matsui on DataCamp. 4 hours.
Day 16
- Joining Data with pandas. A course by Aaren Stubberfield on DataCamp. 4 hours.
Day 17
- Introduction to Statistics in Python. A course by Maggie Matsui on DataCamp. 4 hours.
Day 18
- Exploring and Analyzing Data 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.
Day 19
- 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.
- Importing & Cleaning Data with Python. A DataCamp skill assessment. 10 minutes.
- Data Manipulation with Python. A DataCamp skill assessment. 10 minutes.
- Start Project: Exploratory Data Analysis. Your third project. Completed on DataCamp Workspace using the livestream from Day 3 as a guide. 4 hours.
Day 20
- Finish Project: Exploratory Data Analysis. 4 more hours.
Data Visualization & Statistics
Day 21
- Understanding Data Visualization. A course by Richie Cotton on DataCamp. 2 hours.
- Introduction to Data Visualization with Seaborn. A course by Erin Case on DataCamp. 4 hours.
Day 22
- Intermediate Data Visualization with Seaborn. A course by Chris Moffitt on DataCamp. 4 hours.
Day 23
- Sampling in Python. A course by James Chapman on DataCamp. 4 hours.
Day 24
- 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.
Day 25
- 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.
- Data Visualization Theory. A DataCamp skill assessment. 10 minutes.
- Data Visualization with Python. A DataCamp skill assessment. 10 minutes.
- Statistics Fundamentals with Python. A DataCamp skill assessment. 10 minutes.
- Analytic Fundamentals. A DataCamp skill assessment. 10 minutes.
Day 26
- Start Project: Data Visualization. Your fourth and final project. Completed on DataCamp Workspace using the livestream from Day 3 as a guide. 4 hours.
Day 27
- Finish Project: Data Visualization. 4 more 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.
- 10 Differences Between Amateurs and Professional Analysts. A Medium article by Cassie Kozyrkov. 8 minutes. Free.
And that’s my take on the internet’s best curriculum for aspiring analytics pros in 2023. I invite you to join our community here and start your Initiation to begin forging your journey to data analyst financial freedom.