Data Science Bootcamp | Machine Learning in Python

Overview

Data Science and Machine Learning in Python

This bootcamp is a deep dive into the fundamentals of data science and machine learning in Python. Throughout the course, you will gain a comprehensive understanding of the entire data science process from end-to-end, including data prep, data analysis and visualization, as well as how to properly apply machine learning algorithms to various situations or tasks. You’ll also walk away with a portfolio of projects showcasing your data science acumen to prospective employers!

Coding Dojo Named One of the 10 Most Prominent Data Science Institutes Read the Article

YOUR TEAM

Our Data Science Team

Brenda Hungerford Data Science Instructor

Brenda Hungerford, Lead Instructor, US

Brenda holds a Ph.D. in Curriculum and Instruction, an M.S. in Data Analytics, and an M.Ed. in Math, Science, and Technology. She’s been teaching Data Science for over 15 years.

The instructor could not have been more amazing! She was always helpful, never got frustrated with repetitive or 'dumb' questions, and gave positive reinforcement and encouragement regularly. Cassandra Simmons Coding Dojo Alumni

Curriculum Designers

Michael Galarnyk

Ex-NASA Engineer & Stanford Professor

Noelle Brown

BS / MS in Data Science Over 500 students taught

Explore Data Science Bootcamp

Question? Get Quick Answers

Schedule Admissions Call

1-on-1 call for quick answers about the data science program
Schedule a Call
Join the Open House

Meet the team, see the bootcamp breakdown
Join the Open House

Why Us?

The Dojo Difference

Our mission is to transform lives through learning. We don’t require our students to have a traditional 4-yr degree because we know that there are many paths to sucess. If you are willing to buckle down and do the work, we are here to teach and support you.

	Coding Dojo	Brainstation	General Assembly	Thinkful
NO admissions test
NO 4-yr degree requirement				STEM bachelor's OR 2 years data experience
NO Python or programming experience required

Leveling Up

Curriculum Overview

This bootcamp is a deep dive into the fundamentals of data science and machine learning in Python. You’ll walk away with a portfolio of projects showcasing your data science acumen to prospective employers!

Start

Weeks 1-4
Level one

Weeks 5-8
Level Two

Weeks 9-12
You Win!

Graduation

- Week 1Foundations in Python
  
  Learn the Python fundamentals needed for data science.
  Technologies:
  - Google Collaboratory
  - Python
- Week 2Manipulating & Understanding Data
  
  Learn how to load, clean, and manipulate data using the Python library Pandas. Additionally, you will learn the strengths and weaknesses of using Python to manipulate data.
  Technologies:
  - Numpy
  - Pandas
- Week 3Foundations of Data Modeling & Intro to Machine Learning
  
  Build visualizations to not only understand your data, but also how to communicate results to stakeholders.
  Technologies:
  - Folium
  - Matplotlib
  - Pandas
  - Seaborn
- Week 4Statistical inference
  
  Learn how to use Python to implement key statistical techniques and understand statistics better by experimenting with Python on real-world datasets. This week concludes with a project to showcase your knowledge.
  Technologies:
  - Matplotlib
  - Pandas
  - Folium
  - Seaborn
Week 1Foundations in Python

Learn the Python fundamentals needed for data science.
Technologies:

Google Collaboratory

Python
Week 2Manipulating & Understanding Data

Learn how to load, clean, and manipulate data using the Python library Pandas. Additionally, you will learn the strengths and weaknesses of using Python to manipulate data.
Technologies:

Numpy

Pandas
Week 3Foundations of Data Modeling & Intro to Machine Learning

Build visualizations to not only understand your data, but also how to communicate results to stakeholders.
Technologies:

Folium

Matplotlib

Pandas

Seaborn
Week 4Statistical inference

Learn how to use Python to implement key statistical techniques and understand statistics better by experimenting with Python on real-world datasets. This week concludes with a project to showcase your knowledge.
Technologies:

Matplotlib

Pandas

Folium

Seaborn
- Week 5Introduction to Machine Learning
  
  What is machine learning and why should you use the Python Scikit-Learn for Machine Learning. Topics include types of machine learning, how to format your data to be acceptable for an algorithm, and how to train an algorithm.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 6Decision Trees and Random Forests
  
  Learn about tree based machine learning algorithms, how to tune them to maximize their performance, and the strengths and weaknesses of each algorithm. Additional topics include feature selection for machine learning, and comparing machine learning algorithms.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 7Logistic Regression and Regularization
  
  Learn about the logistic regression algorithm and get a visual understanding of how the algorithm works. Additional topics include: logistic regression for multiclass classification, L1 and L2 regularization, and hyperparameter tuning the algorithms learned so far.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 8KMeans, Hierarchical Clustering, and DBSCAN
  
  What is unsupervised learning and what are its applications. You’ll learn about a host of clustering algorithms, how to tune them, and the strengths and weaknesses of each. This week concludes with a machine learning project to showcase your knowledge.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
Week 5Introduction to Machine Learning

What is machine learning and why should you use the Python Scikit-Learn for Machine Learning. Topics include types of machine learning, how to format your data to be acceptable for an algorithm, and how to train an algorithm.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 6Decision Trees and Random Forests

Learn about tree based machine learning algorithms, how to tune them to maximize their performance, and the strengths and weaknesses of each algorithm. Additional topics include feature selection for machine learning, and comparing machine learning algorithms.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 7Logistic Regression and Regularization

Learn about the logistic regression algorithm and get a visual understanding of how the algorithm works. Additional topics include: logistic regression for multiclass classification, L1 and L2 regularization, and hyperparameter tuning the algorithms learned so far.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 8KMeans, Hierarchical Clustering, and DBSCAN

What is unsupervised learning and what are its applications. You’ll learn about a host of clustering algorithms, how to tune them, and the strengths and weaknesses of each. This week concludes with a machine learning project to showcase your knowledge.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
- Week 9Uses of Dimensionality Reduction
  
  What is unsupervised learning and what are its applications. You’ll learn about a host of clustering algorithms, how to tune them, and the strengths and weaknesses of each. This week concludes with a machine learning project to showcase your knowledge.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 10Gradient Boosting Algorithms and Kaggle Competitions
  
  Learn what gradient boosting algorithms are, why they are so performant, and how to get started with Kaggle competitions.
  Technologies:
  - XGBoost
  - LightGBM
- Week 11Using SQL with Python
  
  Working with databases is an essential part of being a data analyst, data scientist, and data engineer.
  Technologies:
  - SQL
  - SQL Alchemy
  - SQLite
- Week 12Deep Learning Frameworks
  
  Learn about why deep learning has transformed industries, various deep learning frameworks, and when to use deep learning techniques. Topics include recurrent neural networks (RNN) and Convolutional Neural Networks (CNN).
  Technologies:
  - Keras
  - TensorFlow
Week 9Uses of Dimensionality Reduction

What is unsupervised learning and what are its applications. You’ll learn about a host of clustering algorithms, how to tune them, and the strengths and weaknesses of each. This week concludes with a machine learning project to showcase your knowledge.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 10Gradient Boosting Algorithms and Kaggle Competitions

Learn what gradient boosting algorithms are, why they are so performant, and how to get started with Kaggle competitions.
Technologies:

XGBoost

LightGBM
Week 11Using SQL with Python

Working with databases is an essential part of being a data analyst, data scientist, and data engineer.
Technologies:

SQL

SQL Alchemy

SQLite
Week 12Deep Learning Frameworks

Learn about why deep learning has transformed industries, various deep learning frameworks, and when to use deep learning techniques. Topics include recurrent neural networks (RNN) and Convolutional Neural Networks (CNN).
Technologies:

Keras

TensorFlow
- Graduation
  
  You made it! Upon graduation, you have proven yourself as a data wizard. Not only do you possess a portfolio of projects that show off your skills, but you have learned the industry's best practice and tools. You've also tackled plenty of interview-style questions, so you are ready for the job market!

Download Free Course Packet

Support

Here to Support You

Live Instruction

Start each day with live algorithms, discussion sessions, and a group activity.
Office Hours

Lab hours are often where the learning really happens! This is where you can work in groups or solo to create assignments and connect with instructors.
24/7 Cohort Access

From Day 1, you’ll join our Discord community full of your fellow classmates and instructors, as well as have 24/7 access to our Learning Platform.
Student Services Team

If you ever find yourself struggling, reach out to our student services team! They are here to help with time management, tech issues, and more.
TA Support

TA’s are available from 2pm to 7pm PST, Monday through Friday, to line up with when most students are tackling assignments.
Live Lectures

Schedule sessions with your instructor in groups of 2 or 3 to get detailed feedback on milestone assignments

Career Services

Prepare for a New Career

This course was designed to prepare you for the real world. Each week, you’ll tackle interview-style questions and weekly exercises as you learn new topics, so that you are building the skills needed to land a new job as you learn the topics themselves.

No Expiration Date lifetime community + support
Unlimited Support starting day one
One on One mentors

Beginning the Program

What to Expect

Meet your Mentor
Set your Career Goals
Start a Target List

During the Program

What to Expect

Build your Brand
One on One Mentorship
Resume Development
Networking Strategy

Ending the Program

What to Expect

Job Search Strategy
Alumni Network Access
Mock Interview Practice
Contract Negotiation

After the Program

What to Expect

Lifetime Community Support
Mentor Check Ins
Salary Negotiation
Contract Negotiation

I completed both a full-stack Python and Data Science PT bootcamp with Coding Dojo. Can't say enough great things about the school, it's online curriculum platform and relevance to current industry standards. I was fortunate to have both Michael and Noelle as my main instructors through both platforms, and cannot say enough about their patient teaching methods. David Nick Coding Dojo Alumni

89.1%placement within 180 days of graduation
Outcomes you can trust

Our placement statistics have been independently verified by an auditing firm. Download our Outcomes Report.

Payment

Tuition + Financing

Not sure which financing option is right for you? Check out Financing 101 or book a call with admissions!

Pay in Full Pay upfront to save $250 off your tuition $8,745

A $1,000 deposit is also required to reserve your seat.
Installment $1000 deposit $8,995

Installment plans are available via Miashare. All plans carry 0% interest and do not require a credit check.
Ascent $1000 deposit As low as$289 / month

Borrow up to the total cost of tuition. Learn More.
Climb Credit Loan $1000 deposit As low as$178 / month

Apply for a tuition loan in just five minutes with our credit partner, Climb. Qualify for a monthly payment plan customized to your needs.

Scholarships

Fresh Start Fund$1000
Career Re-invention Scholarship$1000
Military Re-training Scholarship$1000
Women in Tech Scholarship$1000
Diversity Scholarship$1000

Fresh Start Fund

Awards $1000, for those making less than $40,000/year

The Fresh Start Fund was established to help prospective students bridge gaps in income or other hardships due to the COVID-19 pandemic.

To apply for the Fresh Start Fund, visit here

Career Re-invention Scholarship

Awards $1000

The Career Reinvention scholarship is intended for experienced professionals who have “hit a wall” and are eager to reinvent their careers, but are unable to afford the professional assistance required to refine their skill sets.

Military Re-training Scholarship

Awards $1000

The Military Retraining Scholarship is intended to assist military veterans and current servicemen/women to transition their careers to web software development.

Women in Tech Scholarship

Awards $1000

The Women in Tech Scholarship is intended for aspiring female computer programmers who require financial assistance to launch their careers. This initiative is offered to support women in the technology industry, who as a demographic are highly underrepresented.

Diversity Scholarship

Awards $1000

The Diversity Scholarship is intended to support and encourage underrepresented groups in the technology industry.

Fresh Start Fund$1000

The Fresh Start Fund was established to help prospective students bridge gaps in income or other hardships due to the COVID-19 pandemic.

To apply for the Fresh Start Fund, visit here
Career Re-invention Scholarship$1000

The Career Reinvention scholarship is intended for experienced professionals who have “hit a wall” and are eager to reinvent their careers, but are unable to afford the professional assistance required to refine their skill sets.
Military Re-training Scholarship$1000

The Military Retraining Scholarship is intended to assist military veterans and current servicemen/women to transition their careers to web software development.
Women in Tech Scholarship$1000

The Women in Tech Scholarship is intended for aspiring female computer programmers who require financial assistance to launch their careers. This initiative is offered to support women in the technology industry, who as a demographic are highly underrepresented.
Diversity Scholarship$1000

The Diversity Scholarship is intended to support and encourage underrepresented groups in the technology industry.
Early Start Scholarship$1000

The Early Start Scholarship is intended for driven and determined freshly graduated high school students and young adults who are eager to get a jumpstart on their careers.

Application Process

How to Enroll

At Coding Dojo, we truly believe that anyone can learn to code, regardless of their professional background. After teaching 6000+ students, we have found that determination is the #1 factor to student success - NOT coding experience. That’s why our admissions process does not include a coding challenge or technical assessment.

Explore (optional)

Schedule a Q&A call with Admissions to get quick answers about the bootcamp or join the next Open House.
Apply

Ready to join? Submit your application and pick your start date to join.
Deposit to Enroll

If accepted, submit your deposit to officially save your seat and gain access to bootcamp-prep materials for your start date.

Upcoming Program Dates

Nov 29, 2021 to Mar 6, 2022 Enroll By Nov 25, 2021 $8,995 Apply Now
Jan 24, 2022 to Apr 17, 2022 Enroll By Jan 20, 2022 $8,995 Apply Now

Still Have Questions?

Attend an Open House

What are you waiting for?

Let’s get started.

Apply Now

Faqs

You've Got Questions We've Got Answers

What is Data Science?

Data science is the process of using data to solve business problems and make informed, cost-effective decisions. Data Science is a combination of statistics, programming, and business knowledge.
What is Machine Learning?

Machine learning is the process of getting a computer (the “machine”) to understand patterns in a dataset (to “learn”) without having to have a human explicitly teach it what those patterns are/should be. At its core, machine learning relies on statistical algorithms. It is the foundation for artificial intelligence.
What is the difference between Data Analytics and Data Science?

One of the main goals of data analytics is to answer questions about the data that we have now - answering the questions of “what happened” and “why did that happen.” Data science takes this a step further, and looks into answering the question of “what is going to happen next?”
Why should I take Data Science at Coding Dojo?

At Coding Dojo, we focus on teaching you the most in-demand, job-ready skills. We truly believe that you learn best by doing, so our assignments and curriculum are built with this in mind.
Is this REALLY beginner-friendly?

Our course is designed with the assumption that you do not have any background in coding, statistics, or data science. However, it is always helpful to have a little bit of practice before starting the course - this is why we offer access to our pre-work as soon as you enroll. Our pre-work is designed to get you up to speed on the fundamentals of Python so you are ready to jump into data science when the course starts.
Will I really be job-ready after 12 weeks?

As with anything, you will get out what you put into the course. Our curriculum is designed to be hands-on and provide you with practice in job-ready skills. Since we focus on the application of data science skills, you can be confident knowing you will come out of the course with the skills necessary to be successful in a job.
How many people will be in my class?

Each cohort typically has between 20 to 30 people.
What happens if it’s too difficult for me and I have to drop out?

If you find yourself struggling, reach out to both your instructor and the student support team. Together, we will do our absolute best to keep you on track and feeling confident about the material.
I don’t have any experience but I really want to get into Data Science; how can I be sure this is for me?

Our program is truly designed with beginners in mind. We believe that anyone can learn data science, and we do not require any test, degree, or background in the field to join our program. We believe that your work ethic, passion, and drive are better indicators of success than the background knowledge you have coming into the class. If you enjoy math, geek out on numbers, and want to learn how to master data - this class is for you!

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Why Us

Curriculum

Who We Are

ONLINE / DATA SCIENCE

Data Science Online Part-Time Bootcamp

Data Science and Machine Learning in Python

Next Program DatesMore Dates

Overview

Data Science and Machine Learning in Python

YOUR TEAM

Our Data Science Team

Brenda Hungerford, Lead Instructor, US

Curriculum Designers

Michael Galarnyk

Noelle Brown

Explore Data Science Bootcamp

Question? Get Quick Answers

Schedule Admissions Call

Join the Open House

Why Us?

The Dojo Difference

Leveling Up

Curriculum Overview

Start

Weeks 1-4

Level one

Weeks 5-8

Level Two

Weeks 9-12

You Win!

Graduation

Week 1Foundations in Python

Week 2Manipulating & Understanding Data

Week 3Foundations of Data Modeling & Intro to Machine Learning

Week 4Statistical inference

Week 1Foundations in Python

Week 2Manipulating & Understanding Data

Week 3Foundations of Data Modeling & Intro to Machine Learning

Week 4Statistical inference

Week 5Introduction to Machine Learning

Week 6Decision Trees and Random Forests

Week 7Logistic Regression and Regularization

Week 8KMeans, Hierarchical Clustering, and DBSCAN

Week 5Introduction to Machine Learning

Week 6Decision Trees and Random Forests

Week 7Logistic Regression and Regularization

Week 8KMeans, Hierarchical Clustering, and DBSCAN

Week 9Uses of Dimensionality Reduction

Week 10Gradient Boosting Algorithms and Kaggle Competitions

Week 11Using SQL with Python

Week 12Deep Learning Frameworks

Week 9Uses of Dimensionality Reduction

Week 10Gradient Boosting Algorithms and Kaggle Competitions

Week 11Using SQL with Python

Week 12Deep Learning Frameworks

Graduation

Support

Here to Support You

Live Learning

Office Hours

24/7 Cohort Access

Student Services Team

TA Support

Small Group Code Reviews

Live Instruction

Office Hours

24/7 Cohort Access

Student Services Team

TA Support

Live Lectures

Live Learning