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Free Data Analytics Bootcamp

  • Learn at your own pace with a flexible curriculum designed for all skill levels.
  • Create real-world data projects to build a portfolio that sets you up for success.
  • Gain a skillset in data manipulation, statistics, machine learning, and visualization.
  • Access 360+ hours of free expert designed content—no costs, no commitments.
Join the Free Course
About the learning track

Learn. Analyze. Visualize. For Free.

This free, fully asynchronous Data Analytics program equips learners with the tools, techniques, and practical knowledge to unlock the potential of data in any industry. Designed for flexibility and accessibility, this program takes you from foundational concepts to advanced analytics, culminating in hands-on projects and portfolio-ready work to showcase your skills.

  • Completely Free with access to 360+ hours of expert-designed content without any cost, no strings attached.
  • Self-Paced & Flexible to learn when it’s convenient for you, with no deadlines or live sessions to attend.
  • Hands-On Labs & Real-World Projects to build a robust portfolio with practice and industry-relevant assignments.
  • Comprehensive Curriculum from From Excel and SQL to Python, Tableau, and machine learning, this program covers all essential skills for data analysts.
  • Career-Aligned Training to develop the technical expertise and critical thinking skills required for a career in data analytics.

You’ll learn the tools and languages data professionals use, like:

Excel
SQL
Kaggle
Tableau
Who is this course for

For Anyone Ready to Explore Tech, No Matter the Stage

This course is for those ready to find a new opportunities, whether you’re taking your first chance at data, considering a career change, or passionate about tech but unsure where to begin. From mastering data manipulation and statistical analysis to building real-world solutions like predictive models and dynamic dashboards, this program meets you where you are. For those juggling life and learning (which is 99% of us), the flexibility to progress at your own pace is key.

You don’t need to have it all figured out yet—what matters is your curiosity and willingness to invest in yourself. This course is here to guide and support you through that journey.

Begin Learning

Aspiring Data Analysts

who want to start their journey into the world of data and analytics.

Professionals Upskilling

who want to learn new tools and techniques to grow in their current role.

Career Changers

who want to transition into a data-focused career with confidence.

Data Enthusiasts

who want to learn to analyze and visualize data for personal projects or curiosity.

Curriculum

What You’ll Learn in This Free Data Analytics Program

Begin Learning

The curriculum is designed to provide a comprehensive, hands-on learning experience, covering essential data analytics concepts, tools, and techniques. You’ll start with foundational topics such as data cleaning, Excel, and SQL, before progressing to advanced areas like machine learning, Python, and data visualization with Tableau. Through hands-on labs and real-world projects, you’ll develop the expertise to build a job-ready portfolio that showcases your ability to analyze and visualize data, and solve complex problems.

Explore the course content

  • Prework

Getting Started

  • 40 hours

Lay the groundwork for your data analytics journey by setting up tools, creating accounts, and completing essential tasks to ensure you’re prepared for advanced analytics training.

In this module, you will learn:

  • How to navigate the command line and install key tools like Tableau and Anaconda.
  • Basics of Excel for data organization and analysis.
  • Setting up accounts on Kaggle, GitHub, and Tableau Public for data-driven projects.

Key elements of this module include:

  • Assignments to complete installations for Excel, SQLite, and VSCode.
  • Excel Prework Assignment to practice data organization.
  • A quiz on navigating the command line.
  • Core Modules

Module #1

Machine Learning - Classification

  • 40 hours

Learn classification techniques to solve real-world problems, from churn prediction to customer segmentation.

In this module, you will learn:

  • How to use K-Nearest Neighbors for classification tasks.
  • Techniques for building and deploying Streamlit apps.
  • Metrics for evaluating classification models.

Key elements of this module include:

  • Labs analyzing datasets like cell phone churn and wine classifications.
  • Assignments on building Streamlit apps for interactive dashboards.
  • A career project: Airline Satisfaction Predictions.

Module #2

Microsoft Excel

  • 40 hours

Master Excel as a tool for data cleaning, transformation, and analysis while exploring advanced techniques for working with datasets.

In this module, you will learn:

  • Data cleaning and transformation techniques in Excel.
  • Applied statistics and visualization using Excel tools.
  • Advanced Excel topics like pivot tables and conditional formatting.

Key elements of this module include:

  • Labs focused on real-world datasets like YouTube trends and BART transit data.
  • A project analyzing bias in home mortgage loans.
  • Interactive assignments on data analysis and reporting.

Module #3

SQL & Relational Databases

  • 40 hours

Develop your skills in querying and managing data using SQL, the foundational language for data analytics.

In this module, you will learn:

  • Querying and filtering data in relational databases.
  • Joining and aggregating data for advanced analysis.
  • Cleaning, organizing, and visualizing data with SQL.

Key elements of this module include:

  • Labs on analyzing real-world datasets, including NBA statistics and traffic collisions.
  • Assignments focused on SQL subqueries and date-time functions.
  • A career project: Chinook Music Store dataset analysis.

Module #4

Basics of R

  • 40 hours

Learn the basics of R programming for statistical analysis, data manipulation, and visualization.

In this module, you will learn:

  • How to work with R’s data structures and packages.
  • Techniques for data visualization using ggplot2.
  • Basic statistical and inferential analysis using R.

Key elements of this module include:

  • Labs on datasets like mtcars and female mice body weights.
  • Assignments to create data visualizations and perform statistical analysis.
  • A project: CO2 Dataset Analysis with R.

Module #5

Introduction to Python

  • 40 hours

Explore Python as a tool for data manipulation and analysis, building essential skills for programming and automation.

In this module, you will learn:

  • Python syntax and data types, including strings, lists, and dictionaries.
  • Control flow, iteration, and functions in Python.
  • How to manipulate datasets and automate workflows.

Key elements of this module include:

  • Labs focused on real-world applications, such as string and list manipulation.
  • Assignments to practice problem-solving with Python.
  • Knowledge checks and coding challenges.

Module #6

Python for Data Analysis

  • 40 hours

Delve deeper into Python’s capabilities for analyzing and visualizing data using libraries like Pandas and Seaborn.

In this module, you will learn:

  • The basics of Pandas for data manipulation and cleaning.
  • How to create data visualizations using Seaborn.
  • Best practices for documenting your projects with READMEs.

Key elements of this module include:

  • Labs analyzing datasets like Titanic passenger data.
  • Assignments on creating project READMEs and exploratory data analysis (EDA).
  • Projects: Higher Education Consulting Analytics and Independent Data Exploration.

Module #7

Machine Learning - Regression

  • 40 hours

Begin your machine learning journey by exploring regression models and their applications in predictive analytics.

In this module, you will learn:

  • The fundamentals of machine learning and linear regression.
  • Techniques for predicting outcomes and submitting models on Kaggle.
  • How to apply regression models to real-world datasets.

Key elements of this module include:

  • Labs on predictive modeling, such as MPG predictions.
  • Assignments on participating in Kaggle competitions.
  • A project: House Price Predictions.

Module #8

Machine Learning - Regression

  • 40 hours

Learn classification techniques to solve real-world problems, from churn prediction to customer segmentation.

In this module, you will learn:

  • How to use K-Nearest Neighbors for classification tasks.
  • Techniques for building and deploying Streamlit apps.
  • Metrics for evaluating classification models.

Key elements of this module include:

  • Labs analyzing datasets like cell phone churn and wine classifications.
  • Assignments on building Streamlit apps for interactive dashboards.
  • A career project: Airline Satisfaction Predictions.

Module #9

Tableau

  • 40 hours

Master Tableau for creating dynamic, interactive visualizations and complete a capstone project that showcases your data analytics skills.

In this module, you will learn:

  • How to build dashboards and visualizations using Tableau.
  • Techniques for joining and transforming data in Tableau.
  • Storytelling with data for impactful presentations.

Key elements of this module include:

  • Assignments on building dashboards for datasets like Superstore and video game popularity.
  • Interactive lessons on advanced Tableau features.
  • A capstone project demonstrating end-to-end analytics capabilities.

Industry Opportunity

Equip yourself with in-demand, future-proof data analytics skills.

68K

Average Salary

For entry level data analysts in the US

ZipRecruiter

$924B

Market Growth Rate

For the global big data analytics market in 2032, from 348.21 billion in 2024.

Fortune Business Insights

36%

Employment Growth Rate

For data occupations from 2021 to 2031.

U.S. Bureau of Labor Statistics

Expected Outcomes

What You Walk Away With

Finish with the expertise and projects you need to succeed.

Data Analytics Expertise

that develops technical skills in data manipulation, statistical analysis, and visualization.

Hands-On Projects

building a portfolio showcasing real-world projects and technical proficiency.

Career Readiness

gaining confidence and skills to step into roles such as data analyst, business analyst, or data scientist.

Comprehensive Knowledge

understanding data workflows from exploration and analysis to machine learning and reporting.

Join the Free Course

Testimonials

Here’s why students choose Coding Temple

I had an incredible experience at Coding Temple. The instructors (Flex team—Brandt, Donovan, and Saint) were not only highly knowledgeable but also incredibly supportive and always available to provide guidance. Their continuous feedback and reassurance boosted my confidence and made me feel like I was making great progress.

Melibeth M.

I was still in my senior year of highschool, but I wanted a head start on my career! Coding Temple made that possible with their flex/self-paced schedule! With this I was able to complete lessons on time whenever it was convenient! Though the work was challenging and humbling, I had the help of fellow peers and instructors who I got to know very well, helping me with whatever issues one may face with code or issues with payment/deadlines! The experience is something that I will never forget and am forever grateful to have taken part in!

Augustine T.

Coding Temple exceeded my expectations and left me feeling well-equipped for my career in coding. I highly recommend it to anyone seeking to dive into the world of software development or looking to enhance their existing skills. I had fun learning from my instructors, who were always happy to help when I was stuck and willing to explain things in different ways if needed. They made learning the material easy.

John C.

I started CT in February and just graduated yesterday. I tried out a couple of bootcamps before CT and knew they just weren’t for me. The culture, the way the curriculum was set up. I LOVED that the student to teacher ratio was about 1:4 (compared to others bootcamps where its about 1:15). Our instructors made it known it is a very fast paced course and set us up for success every step of the way. Id recommend this course to anyone that wants to learn how to code!

Monique V.

FAQ

Frequently asked questions

No formal prerequisites are required to start this course—absolutely anyone can begin, even with zero experience in IT or data analytics. While having some basic computer skills or an IT background can make things a bit easier, it’s not necessary. The course is designed to start with foundational topics, so you’ll build your knowledge step-by-step and feel comfortable as you progress.

This course offers over 360 hours of expertly designed content with a focus on hands-on, real-world experience. Unlike many free resources, it provides a structured curriculum, career-focused training, and practical projects that prepare you for industry certifications and data analytics roles.

Absolutely. The skills you’ll acquire, including data cleaning, visualization, SQL querying, and machine learning basics, are highly applicable to freelance work and personal projects. The hands-on experience gained through real-world projects will help you feel confident and prepared to tackle data-driven challenges, whether you’re analyzing datasets for clients, building dashboards, or launching your own data initiatives.

The curriculum is designed to cover both foundational concepts and advanced skills that are highly relevant to the current data landscape. Through real-world projects and up-to-date tools, it ensures learners are prepared for the ever-evolving challenges of the data analytics field.

If you encounter any challenges, there are ample resources to support you. You can revisit the material, utilize external resources, or reach out to the course community for guidance. The hands-on projects are also designed to reinforce learning and make difficult concepts more accessible.

All free learners will have access to two dedicated discussion channels referred to as study halls. One channel is specific to your learning path, allowing you to collaborate with peers who share your focus. The other is a general channel where you can connect with learners from all of Coding Temple’s free courses. You can also join Zoom rooms to work on projects, share insights, and network in real-time with fellow students!

This course prepares you for various roles in the data analytics field, including Data Analyst, Business Analyst, Data Scientist, and Reporting Analyst. It also provides the foundation to pursue advanced skills and certifications in data analysis, helping you advance in a rewarding career in the data-driven industry.

Absolutely! This course is an incredible first step to dip your toes into both Coding Temple and the data analytics industry. It gives you a chance to explore the field and get a feel for the learning experience, so you can make an informed decision before committing to a bootcamp. It’s a great way to test the waters and see if you’re ready to take the next step toward a more immersive, career-focused program.

When you’re ready to level up your skills, check out our full paid data analytics program for a more immersive, career-focused experience. You’ll get hands-on mentorship, live 1:1 expert sessions, and lifetime career support–all backed by our job guarantee!

Coding Temple believes in the power of education. We have built our curriculum around the most in-demand technologies and paired it with the most effective learning styles to prepare our students to be tomorrow’s leaders in technology.

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