Data Science Bootcamp | Python Machine Learning

Overview

Data Science Bootcamp and Python Machine Learning

This data science bootcamp is a deep dive into the fundamentals of data science and machine learning with 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 certification 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 Coding Dojo Data Science Lead Instructor

Brenda Hungerford Lead Instructor

Ph.D. in Curriculum and Instruction M.S. in Data Analytics M.Ed. in Math, Science 15 years teaching experience

Noelle Brown Coding Dojo Data Science Consultant

Noelle Brown Consultant

BS / MS in Data Science Over 500 students taught PhD Candidate, Computing

Josh Johnson Coding Dojo Data Science Instructor

Josh Johnson Instructor

Master’s in Education AAS, Early Childhood Education 15 years teaching experience

Sherlin Whaley Coding Dojo Data Science Instructor

Sherlin Whaley Instructor

B.S. in Electrical and Computer Engineering Certified in Data Science MS Candidate, Data Science 14 years teaching experience

James Irving Coding Dojo Data Science Instructor

James Irving Instructor

B.S. / M.S. in Neuroscience PhD, Neuroscience Certified in Data Science 2 years teaching experience

Purvi Kansara Coding Dojo Data Science Instructor

Purvi Kansara Instructor

M.S in Computer Science & B.S. in Computer Engineering Specialty in Machine Learning and AI 10+ years teaching experience

Neerja Jhingan Coding Dojo Data Science Instructor

Neerja Jhingan Instructor

Master's in Computer Application, MSIT, & BSIT IBM Data Science Professional Certified 3+ years teaching experience

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

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
Level Three

Weeks 13-16
Level Four

Weeks 17-20
(NEW Stack!)
You Win!

Graduation

- Week 1Python for Data Science
  
  Learn the Python fundamentals needed for data science.
  Technologies:
  - Google Collaboratory
  - Python
- Week 2Pandas for Data Manipulation
  
  Learn how to load, clean, and manipulate data using the Python library Pandas. Additionally, learn the strengths and weaknesses of using Python to manipulate data.
  Technologies:
  - Numpy
  - Pandas
- Week 3Exploratory Visualizations
  
  Build visualizations to support exploratory data analysis (EDA).
  Technologies:
  - Folium
  - Matplotlib
  - Pandas
  - Seaborn
- Week 4Explanatory Visualizations
  
  Use Python to create high-quality graphs to share with stakeholders and communicate key findings.
  Technologies:
  - Matplotlib
  - Pandas
  - Folium
  - Seaborn
Week 1Python for Data Science

Learn the Python fundamentals needed for data science.
Technologies:

Google Collaboratory

Python
Week 2Pandas for Data Manipulation

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

Numpy

Pandas
Week 3Exploratory Visualizations

Build visualizations to support exploratory data analysis (EDA).
Technologies:

Folium

Matplotlib

Pandas

Seaborn
Week 4Explanatory Visualizations

Use Python to create high-quality graphs to share with stakeholders and communicate key findings.
Technologies:

Matplotlib

Pandas

Folium

Seaborn
- Week 5Introduction to Machine Learning
  
  What is machine learning and why use Scikit-Learn for Machine Learning? Topics include types of machine learning and preprocessing data for machine learning.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 6Regression Models
  
  Learn about machine learning algorithms, how to tune them to maximize their performance, and the strengths and weaknesses of each algorithm.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 7Classification Models
  
  Learn about classification metrics, confusion matrices, and how to hypertune classification models
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 8Gradient Boosting Machines
  
  Learn what gradient boosting algorithms are, why they are so performant, and how to get started with Kaggle competitions.
  Technologies:
  - XGBoost
  - LightGBM
Week 5Introduction to Machine Learning

What is machine learning and why use Scikit-Learn for Machine Learning? Topics include types of machine learning and preprocessing data for machine learning.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 6Regression Models

Learn about machine learning algorithms, how to tune them to maximize their performance, and the strengths and weaknesses of each algorithm.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 7Classification Models

Learn about classification metrics, confusion matrices, and how to hypertune classification models
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 8Gradient Boosting Machines

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

XGBoost

LightGBM
- Week 9Clustering Algorithms
  
  Learn about unsupervised learning and its applications. Learn about clustering algorithms, how to tune them, and the strengths and weaknesses of each.
  Technologies:
  - XGBoost
  - LightGBM
- Week 10Uses of Dimensionality Reduction
  
  What is dimensionality reduction? Learn how to use it for data visualization, to speed up machine learning algorithms, and to understand data better. Explore Principal Component Analysis (PCA) and feature engineering techniques.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 11Deep Learning Frameworks
  
  Learn about why deep learning has transformed industries, various deep learning frameworks, and when to use deep learning techniques. Topics include sequential artificial networks, and deep learning regularization.
  Technologies:
  - Keras
  - TensorFlow
- Week 12Introduction to SQL for Data Science
  
  Learn how to perform SQL queries and use SQLalchemy and SQLite.
  Technologies:
  - SQL
  - SQL Alchemy
  - SQLite
Week 9Clustering Algorithms

Learn about unsupervised learning and its applications. Learn about clustering algorithms, how to tune them, and the strengths and weaknesses of each.
Technologies:

XGBoost

LightGBM
Week 10Uses of Dimensionality Reduction

What is dimensionality reduction? Learn how to use it for data visualization, to speed up machine learning algorithms, and to understand data better. Explore Principal Component Analysis (PCA) and feature engineering techniques.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 11Deep Learning Frameworks

Learn about why deep learning has transformed industries, various deep learning frameworks, and when to use deep learning techniques. Topics include sequential artificial networks, and deep learning regularization.
Technologies:

Keras

TensorFlow
Week 12Introduction to SQL for Data Science

Learn how to perform SQL queries and use SQLalchemy and SQLite.
Technologies:

SQL

SQL Alchemy

SQLite
- Week 13Introduction to Databases
  
  Learn the advantages of using a relational database. Learn intermediate SQL queries to access and aggregate information.
  Technologies:
  - SQL
  - SQL Alchemy
  - SQLite
- Week 14Intro to ETL (Extract Transform Load)
  
  Develop an understanding of the process of extracting, transforming, and loading data.
  Technologies:
  - SQL
  - SQL Alchemy
  - SQLite
- Week 15Statistical Analysis
  
  Learn tools for statistical analysis including measures of central tendency, variance and standard deviation and comparing means.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
- Week 16Model Assumptions
  
  Explore model assumptions and how to test for them. Apply this knowledge to choose the appropriate model for a data set.
  Technologies:
  - Matplotlib
  - Pandas
  - Scikit-Learn
  - Seaborn
Week 13Intro to Databases

Learn the advantages of using a relational database. Learn intermediate SQL queries to access and aggregate information.
Technologies:

SQL

SQL Alchemy

SQLite
Week 14Intro to ETL (Extract Transform Load)

Develop an understanding of the process of extracting, transforming, and loading data.
Technologies:

SQL

SQL Alchemy

SQLite
Week 15Statistical Analysis

Learn tools for statistical analysis including measures of central tendency, variance and standard deviation and comparing means.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
Week 16Model Assumptions

Explore model assumptions and how to test for them. Apply this knowledge to choose the appropriate model for a data set.
Technologies:

Matplotlib

Pandas

Scikit-Learn

Seaborn
- Week 17Data Visualization - Model Interpretations & Insights
  
  Learn to extract, visualize, and interpret model importances.
  Technologies:
  - SHAP
  - Lime
  - Pandas
  - Stats Model
  - Scikit-Learn
- Week 18Data Visualization - Time Series Analysis
  
  Identify, pre-process, and plot time series data with Python. Explore statistics, aggregation, and seasonal trends.
  Technologies:
  - Python
  - Pandas
  - Matplotlib
  - Seaborn
  - Stats Model
  - Scikit-Learn
- Week 19Data Visualization - Introduction to Tableau
  
  Transform, explore, and analyze data while creating high-quality visualizations within Tableau.
  Technologies:
  - Tableau
- Week 20Data Visualization - Dashboards in Tableau
  
  Create an interactive data dashboard in Tableau for data storytelling.
  Technologies:
  - Tableau
Week 17Data Visualization - Model Interpretations & Insights

Learn to extract, visualize, and interpret model importances.
Technologies:

SHAP

Lime

Pandas

Stats Model

Scikit-Learn
Week 18Data Visualization - Time Series Analysis

Identify, pre-process, and plot time series data with Python. Explore statistics, aggregation, and seasonal trends.
Technologies:

Python

Pandas

Matplotlib

Seaborn

Stats Model

Scikit-Learn
Week 19Data Visualization - Introduction To Tableau

Transform, explore, and analyze data while creating high-quality visualizations within Tableau.
Technologies:

Tableau
Week 20Data Visualization - Dashboards In Tableau

Create an interactive data dashboard in Tableau for data storytelling.
Technologies:

Tableau
- 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

Live Learning

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

Open Lab 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.

Small Group Code Reviews

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

TA Support

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

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.

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 Datelifetime community + support
Unlimited Supportstarting day one
One on OneCareer Service Manager Coaching

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

Student Success

Mandy Sachs
Data Science Alumni SpotlightGraduated from Coding Dojo 2021
Dany Trainor
Business Analyst Self EsteemGraduated from Coding Dojo 2021
Nikki Ramchander
Data Analyst Western DigitalGraduated from Coding Dojo 2021

Mandy Sachs

Data Science Alumni SpotlightGraduated from Coding Dojo 2021

David Kavanaugh

CS Background MicrosoftGraduated from Coding Dojo 2021

Raden Mantuano

Digital Marketer MyEtherWalletGraduated from Coding Dojo 2021

The Data Science program offered by Coding Dojo is rigorous but very rewarding and so worth the time and money spent! I joined with no background in coding and no understanding of what a Data Scientist does. The curriculum is in-depth, clear, concise, and fun to work around. During the course, you have to complete tasks by the end of the week like reading, assignments, projects, and exams. At times you will feel stuck but there are many code walk-throughs, videos, and solutions that will help you out. Plus the people at Coding Dojo like your instructor, the ta's, and classmates are more than willing to help you out.

Nikitha RamchanderCoding Dojo Alumni

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 NickCoding Dojo Alumni

Coding Dojo's style was perfect for me. Short explanations, decent code examples and then tons of immediate practice followed by a solution on completion of an assignment so you can immediately gauge how well you grasped the material and what you needed to review.

Cassandra SimmonsCoding Dojo Alumni

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

83.8%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 within 10 days of acceptance to save $250 off tuition!
$11,745-$13,745
A $1,000 deposit is also required to reserve your seat.
- 16-week $10,495
- 20-week $12,495
Installment $500 deposit
$11,995-$13,995
Installment plans are available via Miashare. All plans carry 0% interest and do not require a credit check.
- 16-week $11,995
- 20-week $13,995
Ascent $500 deposit Cover up to 100% of tuition less deposit
Borrow up to the total cost of tuition. Learn More.
- 16-week $11,995
- 20-week $13,995
Climb Credit Loan $500 deposit Cover up to 100% of tuition less deposit
Apply for a tuition loan in just five minutes with our credit partner, Climb. Qualify for a monthly payment plan customized to your needs. Take note that it could take up to 5 business days to process.
- 16-week $11,995
- 20-week $13,995

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 8000+ 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.
Interview

Meet an Admission Advisor to make sure you’re ready for the challenges of the program. An acceptance decision will be made within 2-3 business days.
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

Oct 10, 2022 Enroll By Oct 5, 2022
$11,995-$13,995
Apply Now
Nov 7, 2022 Enroll By Nov 2, 2022
$11,995-$13,995
Apply Now
Dec 12, 2022 Enroll By Dec 7, 2022
$11,995-$13,995
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.
How Hard Is Data Science to Learn?

It depends on your skillset coming into the course, but if you’re comfortable with computers and math, you should have no problem learning data science. Don’t think you have to be gifted at math though, simply a decent grasp on statistics and the ability to problem solve and communicate is enough to become a good data scientist.
Does Data Science Require Coding?

Yes, data science does require some coding. Fortunately, we cover that early on in our data science bootcamp. Machine learning through Python is instrumental in becoming a professional data scientist. As the course gets more advanced, you’ll also pick up coding knowledge of SQL and SQLite. Even if you’ve never thought of yourself as a coder, we’re confident our instruction can get you there.
What is the Difference Between Data Science and Data Analytics

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?”
Do I Need Data Science Experience Before Enrolling?

Nope! Our data science bootcamp is beginner and advanced friendly. So whether you’ve never even read an article on data science, or have a data science degree, everyone will start in the same place. The first four weeks of our data science bootcamp will teach you all the basics of your future career.
How Long Does it Take to Learn Data Science?

Our data science courses last 16 to 20 weeks with the expectation that you commit 20 hours of your week to the course. After graduation, you’ll be ready to take on your first UI/UX design job—and you’ll be helped by our career service team when it comes to creating your resume and interview prep.
What Data Science Jobs Can I Get After the Bootcamp?
There are several entry-level data science jobs you’ll be qualified for after finishing the Coding Dojo data science bootcamp. That includes positions like:
- Machine Learning Analyst
- Business Engineer
- Data Scientist
In these roles, you can expect to work on tasks like cleaning and processing data, identifying trends in data, and creating data visualizations.
How Much Does the Data Science Bootcamp Cost?

Depending on the bootcamp you choose, our 16-week or 20-week Data Science program, our tuition ranges from $11,995 to $13,995. All Coding Dojo students are eligible to apply for one of our partial scholarships that reduce the cost of the program.

FOR BUSINESS

Software Development

Data Science

Cybersecurity

UI/UX Design

Resources Free

Online

Onsite

Admissions

Financing

Why Us

Curriculum

Who We Are

ONLINE / DATA SCIENCE

Data Science Bootcamp Online Part-Time

Data Science and Machine Learning in Python 16-WeeksData Science & Visualization 20-Weeks NEW!

Next Program DatesMore Dates

Overview

Data Science Bootcamp and Python Machine Learning

YOUR TEAM

Our Data Science Team

Brenda Hungerford Lead Instructor

Noelle Brown Consultant

Josh Johnson Instructor

Sherlin Whaley Instructor

James Irving Instructor

Purvi Kansara Instructor

Neerja Jhingan Instructor

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

Level Three

Weeks 13-16

Level Four

Weeks 17-20

You Win!

Graduation

Week 1Python for Data Science

Week 2Pandas for Data Manipulation

Week 3Exploratory Visualizations

Week 4Explanatory Visualizations

Week 1Python for Data Science

Week 2Pandas for Data Manipulation

Week 3Exploratory Visualizations

Week 4Explanatory Visualizations

Week 5Introduction to Machine Learning

Week 6Regression Models

Week 7Classification Models

Week 8Gradient Boosting Machines

Week 5Introduction to Machine Learning

Week 6Regression Models

Week 7Classification Models

Week 8Gradient Boosting Machines

Week 9Clustering Algorithms

Week 10Uses of Dimensionality Reduction

Week 11Deep Learning Frameworks

Week 12Introduction to SQL for Data Science

Week 9Clustering Algorithms

Week 10Uses of Dimensionality Reduction

Week 11Deep Learning Frameworks

Week 12Introduction to SQL for Data Science

Week 13Introduction to Databases

Week 14Intro to ETL (Extract Transform Load)

Week 15Statistical Analysis

Week 16Model Assumptions

Week 13Intro to Databases

Week 14Intro to ETL (Extract Transform Load)

Week 15Statistical Analysis

Week 16Model Assumptions