PYTHON DATA ANALYTICS BOOTCAMP

18 WEEKS TO  YOUR NEW CAREER

Proven Student Success

Personal Coaching with Reuven Lerner

Learn Quickly As Part Of A Team

Powerful Training Exercises & Projects

Whether you want to jump-start a new career or improve your current one, you can’t go wrong with Python and Pandas. Companies need people familiar with these technologies to analyze their data, helping them to earn more and spend less.

Joining Reuven Lerner’s bootcamp means that you’ll have one of the world’s top Python trainers as your personal coach — giving you the right balance of structure, support, challenge, and collaboration that’ll help you to master Python, Git, and Pandas in four months.

Want to improve your career in the shortest possible time? Want the kind of personal attention that only a small class can offer? Want to join a bootcamp while keeping a full-time job? Want to join a course that you’ll actually complete?

The fifth cohort of Reuven’s Python Data Analytics Bootcamp starts on June 19th. Learn more about it below, then schedule a coaching call to see if it’s a good fit for you.

IN JUST 18 WEEKS YOU WILL BE ABLE TO…

Write idiomatic Python, using  core data structures and custom functions

Understand and use object-oriented programming techniques to write maintainable code

Use Git and GitHub to collaborate with colleagues and participate in open-source projects

Use NumPy and Pandas to read, clean, analyze, and export real-world data, including date/time data

Create compelling visualizations with Matplotlib, Seaborn, and Pandas

MY STUDENTS LOVE THE BOOTCAMP

Reuven brings together his deep knowledge about the underpinnings of Python and its data handling features to turbo-charge your skill set. Of primary importance is how Reuven teaches NumPy. In these and subsequent lessons, he offers succinct troubleshooting methods for memory problems with large and specialized data sets.

Sara S

All courses and resources for a full year

As a bootcamp student, you’ll have access to all of Reuven’s video courses, newsletters, exercises, office hours, and special lectures — not just during the bootcamp itself, but for the entire year of your subscription.

Want to go into greater depth on a topic during the bootcamp? Or take more advanced courses on a subject that we only touched on, once we’re done? Or perhaps you want to review a topic that we discussed, to really understand it.

The bootcamp is just the start of your Python learning; when you’re done, you’ll be able to improve and sharpen your skills further with many other resources.

A structured, proven syllabus to keep you on track

How often have you purchased an online course, only to let it sit, unwatched, on your computer? PythonDAB is designed to avoid that by combining video courses with twice-weekly live sessions. The goal is for you to not only watch the videos, but to participate in our live sessions — collaboratively solving problems, participating in special lectures, and getting personal, live feedback from Reuven.

The bootcamp even includes two “rest weeks” for you to catch up with material you might have missed. And if, for whatever reason, you don’t complete the bootcamp, or want to review the material? That’s fine — we run two cohorts each year, which means that your annual membership allows you to participate in it twice. 

Live coaching sessions with Reuven

Previous bootcamp participants have said that the best part of the course was the twice-weekly live sessions with Reuven. Typically, one is a “collaboration session,” when we work together to solve exercises. The other session is typically an open Q&A opportunity, where we can review the material, go beyond it, or explore projects that bootcamp participants need help completing.

We have other opportunities for collaboration, as well: We share code (and critique each other’s solutions) in a private forum. We use GitHub to collaborate on projects, to learn how to use it effectively in the workplace. And Reuven gives some special lectures as well, to supplement the video courses.

The skills you need

PythonDAB was designed, from the ground up, to give you the Python and Pandas skills that companies are looking for in new hires. You need to not only write code, but read it and critique it. You need to know how to use GitHub to collaborate with your colleagues, using private branches and pull requests. And you need to know how to work with real-world data, which is messier than what you’ll find in a typical classroom environment.

The last two weeks of the bootcamp are devoted to solving medium-sized problems. You’ll have to wrap your head around messy, real-world data and challenges that integrate the topics you’ve learned in class. You’ll come out of these final weeks with a stronger understanding of data-analysis projects, and how you can (and should) go about solving them.

If you put in the work — watching the videos, doing the exercises, coming to the live sessions, and participating in code reviews — you will finish the bootcamp with a set of skills that are valued and in demand.

Compatible with a full-time job

Some coding bootcamps expect you to drop everything you’re doing, doing nothing but  programming classes for four months. PythonDAB is demanding, yes — but it’s also designed to be doable alongside a full-time job. Many previous participants brought in data sets related to their work, which we were able to integrate into our collaborative projects.

Expect to spend 10-15 hours each week watching videos, doing exercises, and participating in live sessions. Experienced developers (with little or no Python background) will be closer to the 10-hour mark, while people without much coding experience will need closer to 15. 

The two “rest weeks” during our schedule are there to make up for time needed for work or your family. And if you cannot make a live session? They’re all recorded, and are available for any participant to watch after the lve session ends.

If you have a job, but want a better one, the bootcamp is meant for you.

SMALL COHORTS

PREVIOUS KNOWLEDGE

INVEST IN YOUR CAREER

• Week 1 (June 19)

  Week 1: Basics

  Office hours: Launch, introductions, and installation
  Fundamentals, Section 1: Introduction (55 min)
  Fundamentals, Section 2: Basic data types (58 min)
  Fundamentals, Section 3: Strings (83 min)
  Fundamentals, Section 4: Loops (40 min)
  Office hours: Exercises (basic data structures) + Q&A

• Week 2 (June 26)

  Week 2: Container types

  Fundamentals, Section 5: Lists (86 min)
  Fundamentals, Section 6: Tuples (40 min)
  Fundamentals, Section 7: Dictionaries (48 min)
  Fundamentals, Section 8: Sets (29 min)
  Office hours: Exercise (data structures) + Q&A

• Week 3 (June 3)

  Week 3: Comprehensions and files

  Comprehensions, Sections 1+2: List (66 min)
  (Watch sections 3-6 on your own — not required)
  Files, Section 1: Basic operations (94 min)
  Files, Section 2: Writing to files (45 min)
  (Watch sections 3 and 4 on your own — not required)
  Office hours: Exercise (comprehensions and files) + Q&A

• Week 4 (July 10)

  Week 4: Functions

  Functions, Sections 1+2: Intro to functions (25 min)
  Functions, Section 3: Simple parameters (66 min)
  Functions, Section 4: Advanced parameters (73 min)
  Functions, Section 5: Scoping (64 min)
  Functions, Section 6: Advanced functions (38 min)
  Office hours: Exercise (files and functions) + Q&A

• Week 5 (July 17)

  Week 5: IDE + Git

  Office hours: Using PyCharm
  Git, Section 1: Intro to Git (36 min)
  Git, Section 2: Staging and committing (37 min)
  Git, Section 3: Git logs and status (37 min)
  Git, Section 4: HEAD and commits (24 min)
  Office hours: Exercise (Working with Git) + Q&A

• Week 6 (July 24)

  Week 6: Git and GitHub

  Office hours: Git and GitHub
  Git, Section 5: Fixing mistakes (27 min)
  Git, Section 6: Git objects (15 min)
  Git, Section 7: Branches (46 min)
  Git, Section 8: Merges (88 min)
  (Watch section 9 on your own — not required)
  Git, Section 10: Network (75 min)
  Office hours: Exercise (GitHub and collaboration) + Q&A

• Week 7 (July 31) REST WEEK

  Enjoy the week off and get ready for more learning.

• Week 8 (August 7)

  Week 8: Modules and packages

  Starting this week:
  – We’ll encourage collaborative solving of exercises
  – Exercise solutions will be shared publicly on GitHub
  – Everyone should give at least two comments on others’ code

  Modules, Section 1: Importing (39 min)
  Modules, Section 2: Writing (48 min)
  Modules, Section 3: PyPI (30 min)
  (Watch sections 4, 5, 6, and 7 on your own — not required)
  Office hours: Using modules and venvs with PyCharm + Q&A

• Week 9 (August 14)

  Week 9: Intro objects

  Objects, Sections 1+2: Intro, defining classes (79 min)
  Objects, Section 3: Methods (57 min)
  Objects, Section 4: Class attributes (31 min)
  Objects, Section 5: Inheritance (32 min)

  Optional: Sections 6 and 7

• Week 10 (August 21)

  Week 10: NumPy and intro Pandas

  NumPy, Sections 1+2: Introduction (60 min)
  NumPy, Section 3: Indexing (39 min)
  NumPy, Section 4: Data types (34 min)
  NumPy, Section 5: nan (21 min)
  (Watch section 6, 7, and 8 on your own — not required)
  Pandas, Sections 1+2: Series (53 min)

• Week 11 (August 28)

  Week 11: Pandas series

  Pandas, Section 3: dtypes and NaN (39 min)
  Pandas, Section 4: Advanced series (35 min)
  Pandas, Section 5: Strings (36 min)
  Pandas, Section 6: Plotting series (56 min)

• Week 12 (September 4)

  Week 12: Data frames

  Pandas, Section 7: Data frames (82 min)
  Pandas, Section 8: Boolean indexes (81 min)
  Pandas, Section 9: Reading/writing files (91 min)

• Week 13 (September 18)

  Week 13: Analysis with Pandas

  Office hours: Exercises
  Pandas, Section 10: Analysis (34 min)
  (Watch section 11 on your own — not required)
  Office hours: Dates and times in pandas
  Pandas, Section 12: Indexes and multi-indexes (34 min)
  Additional exercises

• Week 14 (September 25) REST WEEK

  Enjoy some rest and refresh your mind.

• Week 15 (October 2)

  Week 15: Sorting, merging, grouping — and visualization

  Pandas, Section 13: Sorting, merging, and grouping (48 min)
  Pandas, Section 14: Plotting and data frames (42 min)
  Additional exercises

• Week 16 (October 9)

  Week 16: Pandas practice

  This week, we’ll do numerous exercise with pandas. There will be
  two sessions of office hours to discuss and review them.

• Week 17-18 (October 16)

  Pandas Practice & Office Hours