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Master Data Analytics at App Academy

Transform your career with our comprehensive data analytics program. Graduate job-ready in 6 months or less with hands-on experience in Python, SQL, Tableau, and machine learning.

  • 4.8/5 Rating from 750+ Alumni
  • Graduate in 6 months or less
  • 340+ Hours of Live & Asynchronous Learning
  • Job Guaranteed
  • 9 Core Modules + Capstone Project
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Train for Data Analytics on Your Terms

Our Data Analytics Program sets you up for a job-ready future with flexible options that don’t sacrifice quality. Powered by Coding Temple, this program prepares you with expert skills in SQL, Python, data visualization, and machine learning, with a job guarantee to back it up. Whether you choose a live part-time track or a flexible blended learning path, you’ll graduate with hands-on experience and a portfolio that stands out.

Gain Expertise in SQL, Python + Tableau

Build confidence with hundreds of hours of hands-on data skills, including databases, data cleaning, and visualization tools employers rely on.

Thrive with Mastery-Based Data Learning

Our approach helps you master essential data analytics skills in a supportive, challenging, and interactive environment that builds confidence from day one.

Build a Portfolio That Gets You Hired

Create data dashboards, business reports, and predictive models to showcase real-world skills that make you stand out to hiring managers

Launch a Data Analytics Career with Confidence

Access career coaching, interview prep, and lifetime job support to help you land your dream analytics role — backed by our job guarantee.

A FEW OF THE 2,000+ COMPANIES WHERE OUR GRADS WORK

We’ve Got Your Back

Beyond class hours — even on weekends — you’ll get live support and on-demand help from our instructors and teaching assistants. You’ll also have access to student success managers, career coaches, and a dedicated community of fellow learners so you never feel stuck. We’re here to guide you through every challenge, every step of the way.

One Flexible Path, One Goal: Your Data Analytics Career

Part-Time Live Track

Duration: 5 months
Schedule: Mon-Thu, 5:30-9:30 PM CT
Time Commitment: 40 hrs/week
Next Cohort: July 15, 2025

Join our fully live, online bootcamp designed for total immersion. Learn through daily live instruction, interactive sessions, and real-time support — all led by expert instructors. It’s a high-intensity, fast-track experience designed to keep you moving forward.

Blended Learning Track

Duration: Up to 6 months
Schedule: Flexible, self-paced
Time Commitment: 20 hrs/week
Start: Anytime

Get the best of both worlds — the flexibility to learn at your own pace with a clear 6-month timeline and access to live sessions, mentorship, and hands-on help whenever you need it. Ideal for learners balancing other commitments.

What Makes Us Different

Gain industry-ready skills with a powerful blend of live instruction, hands-on projects, and AI-enhanced tools designed to help you confidently launch your data analytics career. Over 340 hours of comprehensive training ensure you master both the tech and the mindset needed to thrive in a data-driven world.

Apply what you learn immediately by working on projects that mirror real industry scenarios, helping you build a portfolio you can show employers.

Access flexible, on-demand content that fits your schedule, allowing you to dive deeper and revisit materials whenever you need.

Participate in guided workshops and get personalized support from technical coaches to overcome roadblocks and solidify your understanding.

Pull together everything you’ve learned in a final project that tackles a realistic, multifaceted data problem — a true showcase for your skills. 

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Become a Data Analyst

Get trained for the job you actually want.

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Change your career with a click

This won't be a solo journey

With Coding Temple’s roster of experts, you’ll be backed by a dedicated team that’s with you every step of the way. From instructors to student success managers and career coaches, you’ll have constant support while collaborating with your classmates on hands-on projects.

Instructors

Industry pros who bring deep data analytics expertise and real-world experience to guide you through every module.

Career Coaches

Specialists who work with you one-on-one to build your resume, prep for interviews, and land your dream job.

Student Success Managers

Your personal cheerleaders who help you stay on track, manage your schedule, and make the most of your learning journey.

Peer Collaboration

Collaborate with fellow learners who will team up with you to solve challenges, share insights, and grow together.

Master Data Analytics in Just 4 Months

Our Data Analytics Bootcamp is designed to equip you with the skills and tools used by data professionals, blending live instruction, hands-on projects, and expert mentorship to ensure you gain real-world experience. This program provides structured learning, guiding you from data fundamentals to advanced analytics techniques.

Core Curriculum

This module builds a strong base in the core principles of data analysis, including statistical theory, data ethics, and essential analytical tools. Students explore the full analytics process—from managing raw data to drawing insights—while also being introduced to modern tools that streamline and enhance analysis through automation and intelligent recommendations.

Key Elements of the Module Include:

  • Data Analytics Fundamentals: Understanding the basics, applications, and ethics of data analytics.
  • Role Differentiation: Distinguishing between Data Analysts, Data Scientists, and Data Engineers.
  • Data Handling and Analysis: Managing datasets, calculating descriptive statistics, and analyzing variable relationships.
  • Data Visualization and Interpretation: Visualizing data distributions, interpreting probability distributions, and conducting hypothesis testing.
  • Integrating Intelligent Tools in Analytics: Explore how smart tools assist with practice generation, insight validation, and critical evaluation, while reinforcing when and why manual analytical skills still matter.

This module immerses students in Excel, starting with foundational tasks and advancing toward real-world data analysis applications. From data cleaning and formatting to statistical modeling and visual storytelling, students gain hands-on experience using Excel’s core capabilities, alongside emerging tools that bring intelligent automation into the workflow.

Key Elements of the Module Include:

  • Excel Proficiency: Navigate Excel’s interface, apply functions for calculations and formatting, and manage missing data and duplicates.
  • Data Analysis and Visualization: Use logical functions, create basic charts and graphs, and perform statistical analysis, including linear regression.
  • Advanced Excel Features: Utilize XLOOKUP, construct pivot tables and charts, and execute A/B tests for data-driven decision-making.
  • Data Standardization and Manipulation: Standardize data formats, perform text manipulation, and create detailed visual representations like histograms and boxplots.
  • Mastering Modern Analytics with Office 365 Tools: Explore how integrated tools like Excel Ideas, Flash Fill, and data types can automate analysis, enhance accuracy, and simplify complex tasks, bringing a layer of intelligence into everyday spreadsheet work.

This module introduces students to the structure and function of relational databases, focusing on how SQL is used to store, query, and manipulate data. Students learn how to build databases from the ground up, write complex queries, and work with large datasets in modern environments, while also exploring the evolving role of intelligent systems in query generation and validation.

Key Elements of the Module Include:

  • Database Concepts and Normalization: Understand database concepts, the relational database model, and normalization techniques for efficient data organization.
  • SQL Query Proficiency: Write and execute SQL queries (SELECT, INSERT, UPDATE, DELETE) and utilize advanced techniques like JOIN operations, subqueries, and aggregate functions.
  • Cloud-Based SQL Execution: Execute SQL queries and manipulate large datasets within cloud-based platforms like BigQuery.
  • Database Management and Analysis: Create and modify database tables, define data types, set constraints, and apply SQL for comprehensive data analysis and insight extraction.
  • Intelligent Assistance and Human Expertise in SQL: Explore how AI tools can help generate, validate, and refine queries, while identifying the core logic, strategy, and critical thinking skills that remain uniquely human and irreplaceable in the data analysis process.

This module introduces students to R, a powerful language for statistical analysis and data visualization. Through hands-on coding and real-world projects, students learn to manipulate data, conduct complex analyses, and create insightful visuals—while also gaining exposure to modern tools that support code generation, optimization, and debugging.

Key Elements of the Module Include:

  • R Environment and Syntax: R Set up the R environment and understand R syntax, including installing and utilizing packages for additional functionalities.
  • Data Manipulation and Cleaning: R Use dplyr and tidyr for data manipulation, cleaning, filtering, sorting, and transformation.
  • Statistical Analysis and Interpretation: R Perform descriptive statistics, hypothesis testing, correlation analysis, regression analysis, ANOVA, and time-series analysis, and interpret results for real-world tasks.
  • Data Visualization: Create diverse types of plots and customize visualizations using ggplot2.
  • Intelligent Support in R Programming: Learn how modern tools assist with code generation, package selection, and debugging, while developing the judgment to validate outputs and understand which skills remain uniquely human in statistical programming.

This module offers a comprehensive introduction to Python programming, covering everything from basic data types to more advanced coding techniques. Students build a strong foundation in writing clean, efficient code and preparing for more complex programming and data analysis tasks, while also learning to navigate the balance between manual problem-solving and automated support.

Key Elements of the Module Include:

  • Pandas Data Manipulation: Understand Pandas data structures, perform data cleaning and preprocessing, and handle missing values and categorical data.
  • Exploratory Data Analysis (EDA): Conduct basic and advanced EDA, select data subsets, and compute descriptive statistics.
  • Data Visualization: Create and customize diverse visualizations, including bar graphs, histograms, scatter plots, line plots, heat maps, and box plots.
  • Project Documentation: Craft informative README files detailing project purpose, functionality, installation instructions, and usage guidelines.
  • Accelerating Analysis with Intelligent Tools: Use assistants like Pandas AI, Jupyter AI, and other generative tools to enhance EDA, automate repetitive tasks, and validate your approach, while sharpening your judgment on what requires manual precision and human insight.

This module introduces students to machine learning fundamentals with a focus on linear regression. Through real-world prediction tasks and hands-on practice—including Kaggle competitions—students develop both the technical and collaborative skills required to build, refine, and communicate predictive models in modern data environments.

Key Elements of the Module Include:

  • Machine Learning Fundamentals: Understand core concepts of machine learning and differentiate between types, with a focus on supervised learning.
  • Linear Regression Modeling: Apply linear regression for predictive modeling, interpret assumptions and coefficients, and make predictions using regression models.
  • Real-World Applications: Apply machine learning techniques to real-world challenges, such as predicting concrete strength and home sale prices.
  • Advanced Regression Techniques: Handle multicollinearity, fine-tune model parameters, and understand advanced techniques like polynomial regression and regularization (Ridge and Lasso).
  • Collaboration and Communication in AI-Augmented Workflows: Work effectively on team projects that involve automation and AI tools, maintain clear documentation, and practice communicating the role and limitations of AI to both technical and non-technical stakeholders, fostering collaboration and informed decision-making.

This module focuses on mastering Tableau to turn raw data into clear, interactive dashboards that support data-driven storytelling. Students learn to design compelling visuals, apply best practices, and create dynamic dashboards—while also gaining exposure to built-in intelligent features that accelerate analysis and insight delivery.

Key Elements of the Module Include:

  • Classification in Machine Learning: Understand classification concepts and evaluate models using confusion matrices and metrics like accuracy, precision, recall, and specificity.
  • K-Nearest Neighbors (KNN): Implement the KNN algorithm for classification tasks and analyze real-world datasets such as the Iris and breast cancer datasets.
  • Data-Driven Decision Making: Extract insights from customer behavior data to inform decisions in industries like telecommunications.
  • Streamlit Applications: Create and deploy interactive web applications using Streamlit for seamless sharing and user accessibility.
  • Enhancing Modeling with Intelligent Tools: Use platforms like PyCaret and AI-powered visualization libraries to accelerate model building and insight generation, while reinforcing critical machine learning skills that require human judgment, domain knowledge, and contextual reasoning.

This module focuses on mastering Tableau to turn raw data into clear, interactive dashboards that support data-driven storytelling. Students learn to design compelling visuals, apply best practices, and create dynamic dashboards—while also gaining exposure to built-in intelligent features that accelerate analysis and insight delivery.

Key Elements of the Module Include:

  • Introduction to Tableau: Get started with the basics of Tableau and its interface.
  • Data Visualization Best Practices: Learn techniques for creating clear and effective visualizations.
  • Building Simple Dashboards: Create your first dashboards to display data insights.
  • Advanced Chart Types in Tableau: Explore a variety of chart types to present data in more dynamic ways.
  • Building Interactive Dashboards: Develop interactive dashboards that allow users to explore data.
  • Embedding and Sharing Dashboards: Learn how to embed dashboards in external platforms and share them with stakeholders.
  • Leveraging Smart Features in Tableau: Use built-in tools like Ask Data, Explain Data, and AI-assisted data prep to speed up analysis and uncover trends—while learning to validate results and apply design logic that AI can’t replicate.

Capstone Project

Get hands on experience as a data professional. Tackle real-life data problems, enhancing your critical thinking and data skills. Apply agile analytical methods, mirroring industry-standard practices. Receive and implement feedback from mentors and peers to refine your skills.

Invest in Your Future

Financing Options

We believe finances shouldn’t hold you back from launching your data analytics career. That’s why we offer flexible payment plans, including zero-deposit options, deferred tuition, and upfront discounts to fit your budget and goals.

Most Savings

Total tuition before discount

$16,000

Discount

-$7,000

Paid at enrollment

$1,000

Pay up front and save 28% on tuition

$16,500

$9,500

Most Flexible

Total tuition before discount

$500/mo

Discount

-$100/mo

Deposit

$250

0% interest and no credit check

$500/mo

$400/mo

Most Popular

Total tuition before interest

$16,500

Discount

-$2,000

Enroll now, pay later. No deposit required.

$16,500

$14,500

Start an Application
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Our Application Process

We’ve designed a process that helps us understand you, your motivations, and your goals. Our process encourages diversity by providing a fair playing field regardless of your background. We look forward to meeting you!

01

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!

02

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.

03

Speak with an Admissions Advisor

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

04

Secure your Seat and Enroll

Finalize your payment plan to secure your seat! Once enrolled, you will gain instant access to our preparatory work, slack channels, and 1:1 support before starting the course work.

Start an Application

FAQs

Questions, Concerns or something else?

What is data analytics?

Data analytics is about examining and evaluating raw data to extract meaningful insights that support intelligent decision-making. You will learn how to turn raw data into meaningful insights, explore beginner and intermediate statistics, and coding basics for data manipulation and analysis techniques. Coding Temple’s data analytics course will turn you into an adept data analyst, ready to tackle the challenges of today’s data-driven world.

What career opportunities exist for data analytics professionals?

Data analytics is rapidly growing across industries like finance, healthcare, and technology. Entry-level roles like Data Analyst or Business Analyst offer competitive salaries ranging from $70,000 to $120,000, while advanced positions in data science can exceed six figures. With our hands-on curriculum, you’ll be prepared to thrive in this high-demand career path.

Is data analytics difficult to learn?

Our data analytics program is designed for people with no prior coding or analytics experience. While challenging and fast-paced, the curriculum is rewarding with supportive instructors always available for guidance. The small student-to-teacher ratio (about 1:4) allows for personalized attention and support.

Ready to change your life?

Become a Data Analyst. Build skills that get you hired.

Start an Application

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