Immersive Data Analytics bootcamp

Become a Data Analyst using the most sought-after curriculum in the industry!

  • 10 weeks | 100% online | Live instruction 10 weeks | 100% online | Live instruction
  • Beginner & advanced friendly Beginner & advanced friendly
  • Job guaranteed Job guaranteed

Get the Immersive Data Analytics coursebook

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Upcoming Cohort Start Dates

Open

November 6, 2023 - January 19, 2024

Open

January 15, 2024 - March 29, 2024

300+

PLACEMENT PARTNERS

86%

GRADUATION RATE

$81,310

AVERAGE SALARY

$23k

SALARY INCREASE

Skills & technologies covered

Curriculum

Skills & technologies covered

Skills & technologies covered

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MODULE 0 / WEEK 0

Onboarding

Get ready for your upcoming Cohort through planful preparation. It is essential to your success as a Student that you attend Pre-Work Sessions, meet with your Onboarding Specialist, perform a tech check, attend orientation, and complete your Pre-Work before the first day of Class. You must plan an entire week set aside for these tasks and take the time needed to prepare yourself to hit the ground running on day 1.

Technologies Used

HTML 5, CSS 3, Bootstrap, Visual Studio Code, git, GitHub, Python

Skills Learned:

Needed Installations, Command Line, Introduction to HTML, CSS, VS Code, git, Github, and Python

Module 1

Intro to Analytics, Stats & Excel

Learn the big picture of data roles, and how they fit together. Understand what a data analyst does specifically and how it differs from data engineers, scientists, and machine learning engineers. Gain a cursory understanding of statistics and tabular data, and the importance of data. Students will be able to explain the difference between continuous and discrete data, as well as the differences between experimental and observational data collection. They’ll also be oriented to the full course and how to use the CT Self Paced model of education. This section will also include how to use slack, google classroom, course etiquette and norms, as well as the installs required to make the course work.

Technologies Used

Basic statistics, career orientation, course goals

MODULES 2, 3, & 4

Python

The first of these two modules will be focused on basic python programming. This will be the same curriculum as our full-stack self-paced course, where we learn data types, writing and executing custom functions, we will get started with scripting in module 2 with Python. This module will get you up to speed on the core concepts of programming using Python’s elegant, easy-to-learn syntax. You’ll learn about looping, conditional statements, data types, object-oriented programming, and more – culminating in a series of small Python applications like shopping carts and interactive games. The second module of Python will focus on doing data analysis with Numpy, Pandas, Matplotlib, and Scipy. We’ll also pick up Regular Expressions, Beautiful Soup for web scraping, and actually automating Excel with Python.

Technologies Used

Python, Numpy, Pandas, Matplotlib, SciPy, RegEx, Beautiful Soup, Automations, Jupyter Notebook

Skills Learned:

Python, Data analysis with python, automation, web scraping

Module 5

Databases & SQL

Build, query, sort and update relational databases in module 4 with SQL. We’ll make our own functions to help automate SQL processes as well. Students will learn about making entity relationship diagrams, the importance of planning ahead when it comes to databases, and how certain data relates to other data. Most tabular data lives in SQL databases, so we will need to be very familiar with this language to explore our data. We’ll look at moving data back and forth between SQL and Excel as well using CSV files. We will build a very good foundational understanding of relational databases, and then practice SQL repeatedly to achieve intermediate SQL fluency. We will also look at a few advanced SQL techniques. We’ll also look a bit under the hood at how PostgreSQL works, and what other kinds of relational databases exist.

Technologies Used

DBeaver, PostgreSQL

Skills Learned:

Entity Relationship Diagrams, Relational Databases, Advanced Querying, Database Management

Module 6

Dashboarding

Module 6 equips learners with skills in data visualization using Tableau and Streamlit. In Tableau, learners master dashboard creation, diverse charting, and data connectivity, including SQL. Streamlit training encompasses Python-based dashboard development for effective, polished online presentation. The module also introduces MongoDB, providing insights into non-relational databases.

Technologies Used

Tableau, Streamlit, MongoDB

Module 7

Data Analysis with R

A programming language specifically meant for use in statistics, we will review most of the concepts in the rest of the course, particularly statistics, in R. Students will learn the basics of the programming language, as well as R’s counterparts to Python’s libraries – Learners will be engaged with ggplot2, tibbles, dplyr, and the tidyverse as well as basic operations, data structures, and more. This module will primarily be used to discuss exploratory data analysis as well.

Technologies Used

R, RStudio, Jupyter Notebook, dplyr, ggplot2, tidyverse

Skills Learned:

Data analysis, R, Rstudio, dplyr, ggplot2, tidyvers

Module 10

Capstone Projects

There will be two capstone projects for this course with two different focuses.

Project 1: Parallel Analysis Report Project 1: Parallel Analysis Report

In this project, students will be expected to find a data set to analyze, and then do so in Python, R, and SQL/Excel if possible. Students will perform the same analysis in all three languages with the goal of understanding the subtle differences between the three tools. After forming a hypothesis, they will explore the data, and this work will culminate in a written report detailing the exploration process, as well as pros and cons of each platform for the analysis. The report will be written as if it is being sent in to a business or research entity as a cumulative response to the hypothesis.

Project 2:  Analysis Presentation  Project 2: Analysis Presentation

A huge part of analysis will be explaining and communicating data to people who don’t speak data. In this project, students will choose a database and language (R, Python, or SQL/Excel) and explore a data set after creating a hypothesis about it. After spending time in the data, they will create a presentation, and then use Loom or similar software to explain the results of the search in a 5-10 minute pre-recorded presentation.

Module 11

Career Readiness

You graduated, Congratulations! Now, the real work begins. This is where you will work with our Career Services team to make sure you are ready to start applying for jobs. They will be there to support you every step of the way through coding assessments, mock interviews, mock whiteboard sessions, resume reviews, LinkedIn reviews, workshops, AI learning, and more. Once you complete the needed requirements, you will be given access to Huntr to support your job search and have access to the team for any job search-related needs.

Technologies Used

CoderPad, ChatGPT, LinkedIn, Huntr

Skills Learned:

Coding Assessments, Resume Preparation, Interviewing Skills, LinkedIn Best Practices, Job Search, Harnessing the Power of AI for your job search

Dive deeper into our Full-Time curriculum

Schedule

Daily schedule

You’ll get a full, immersive experience with your classmates and instructors in an online classroom. You’ll learn to program through a mix of live instruction, coding exercises, and team projects. We’re flexible in how we run our bootcamp, but here’s an example of what a typical day might look like in our Full-Time Cohorts.

9:00 AM
9:30 AM
10:30 AM
12:00 PM
1:00 PM
4:00 - 5:00 PM

Morning review

The morning opens with a chance to interact with other students and teachers, as well as a great opportunity to ask questions and get last minute advice on projects.

Whiteboard algorithms

Starting in Week 2, the class will work through a coding algorithm question to prepare for technical interviews. One student will be chosen to share their screen as they code a solution, talk through their thought process, and get feedback from their instructors on how they solved the problem.

Morning lecture

In a live instruction class, your Senior Instructor will explain concepts and then lead you through how to apply them in real-life scenarios. Often these classes will be broken up into smaller groups so that you can work on projects together or help each other out with solutions.

Break

You will take a 60-minute break to recharge and refuel. Many of our students take advantage of this time to grab lunch, get some exercise, and get back in the right frame of mind for the rest of the day.

Afternoon lecture

The afternoon consists of a continuation of live instruction from your Senior Instructor.

Post lecture review

Your Associate Instructor will lead an hour-long help and review session. These sessions will focus on a different topic or problem-solving technique and are designed to build upon your existing knowledge of the course material.

9:00 AM

Morning review

The morning opens with a chance to interact with other students and teachers, as well as a great opportunity to ask questions and get last minute advice on projects.

9:30 AM

Whiteboard algorithms

Starting in Week 2, the class will work through a coding algorithm question to prepare for technical interviews. One student will be chosen to share their screen as they code a solution, talk through their thought process, and get feedback from their instructors on how they solved the problem.

10:30 AM

Morning lecture

In a live instruction class, your Senior Instructor will explain concepts and then lead you through how to apply them in real-life scenarios. Often these classes will be broken up into smaller groups so that you can work on projects together or help each other out with solutions.

12:00 PM

Break

You will take a 60-minute break to recharge and refuel. Many of our students take advantage of this time to grab lunch, get some exercise, and get back in the right frame of mind for the rest of the day.

1:00 PM

Afternoon lecture

The afternoon consists of a continuation of live instruction from your Senior Instructor.

4:00 - 5:00 PM

Post lecture review

Your Associate Instructor will lead an hour-long help and review session. These sessions will focus on a different topic or problem-solving technique and are designed to build upon your existing knowledge of the course material.

Support

We set students up for success

Dedicated Student Relations Manager

Dedicated Student Relations Manager

Evening and weekend TAs

Evening and weekend TAs

Live instruction

Live instruction

Individualized attention

Individualized attention

Slack community

Slack community

Fine-tune your communication

Fine-tune your communication

Build your personal brand

Build your personal brand

Sharpen your technical skills

Sharpen your technical skills

Leverage our employer network

Leverage our employer network

Build a meaningful community

Build a meaningful community

Utilize resources and templates

Utilize resources and templates

Careers

We offer lifetime career services

Our post-graduation services provide each student with the necessary resources, tools, and guidance to build a meaningful career. We provide 1-1 support for the entirety of your professional journey.

Learn more
Quick Questions

Our Admissions Representatives are ready to help

We’ll work 1-1 to get your questions answered.

We’re here to help you understand our curriculum and financing, as well as give you information about post-graduation services.

Quick Questions

Attend one of our Weekly Webinars

See what our program is like and learn how to get started.

Ask questions during our live Q&A.

Curriculum Reviews

Don’t just take our word for it. Hear from our

Full-Time Data Analytics graduates

Five Stars

"Coding Temple is a fantastic, immersive, and very personal experience! The student-to-instructor ratio is amazing at about 6-to-1. Each day was filled with many hours of learning new technologies and actual coding experience with challenging homework each night and full-fledged weekend projects too."

Steve M.

Five Stars

"I'm a recent graduate of the full-time full-stack + data science program at Coding Temple (remote). Why Coding Temple over the others? The staff! The staff was helpful before, during, and still after the program is complete. They really want you to succeed but you get what you put into it like most things so be prepared. The curriculum was intense but doable if you commit yourself. Full-time means full-time so all of my free time was spent doing homework and projects. What I didn't expect was developing bonds with the other students that were and still are a great support system to this day. Send Coding Temple an email or give them a call, what do you got to lose?"

Steve Y.

Five Stars

"I attended Coding Temple after getting a bachelors in a computer science program at a university and I'm very glad that I did. We covered more ground with hands-on practical programming and theory than we did in my bachelors degree. College really lacked in experience creating real projects and coding with frameworks. Coding Temple filled in all the gaps I had from college and gave me a real portfolio to showcase to employers. While interviewing for jobs, 90% of what was discussed what what I did in the bootcamp, what I made, what I used, and how I did it. I did not get this in college."

Matthew W.

Five Stars

"The quality of the course and the resources you have access to after graduation is worth every penny. In fact it's almost a steal. I haven't compared Coding Temple's alumni support to other bootcamps because I don't need to. I have everything I need to succeed and more. Take this course, put in the effort, and enjoy the success."

Garrett G.

Program cost

Tuition + payment plans breakdown

Pay in full

$1,000 deposit / due prior to 1st day of class

$11,500

Pay as you learn

$1,000 deposit / 3 installments made throughout the class

$12,000

$4,000 week 1, week 4, week 8
All plans carry 0% interest and do not require a credit check.

Deferred tuition

$0 deposit / monthly payments as low as $399

$12,500

Apply for a tuition loan in just five minutes with our
credit partner, Ascent.

Admissions process

How to get started

1

Explore our career paths and courses

Ready to start your new career in tech? Explore our different career tracks and see which path interests you the most!

Explore Courses
2

Schedule an admissions call

Talk with our admissions team so we can get to understand your career goals and answer any questions you have about our program.

Schedule a Call
3

Application and basic skills assessment

Submit your application – it takes less than 5 minutes. After you apply you will be sent a basic skills assessment. Our 50-question assessment is meant to test your cognitive skills. Don’t stress! We want to know if you can think like a programmer, if you can we will take it from there!

Apply Now
4

Secure your seat and enroll

Finalize your payment plan to secure your seat! Once you’re enrolled, you will gain instant access to our preparatory work, slack channels, and 1:1 support prior to class.

See Payment Plans

Not sure if Full-Time is for you?

FAQs