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LAUNCH YOUR CAREER IN GENERATIVE AI

Become a Certified Generative AI Data Analyst with our 12-week immersive bootcamp. Experience live, online classes with generative AI experts and 1:1 coaching. Develop skills in machine learning, data visualization, and AI model training that translate into the AI Data analyst career you deserve.

  • Duration 12 Weeks
  • Upcoming Part-Time Cohort February 24, 2025
  • Price $6,000 (Prepay discount available)*

According to recent data, the AI and Data Analytics market is experiencing significant growth, with estimates showing that the global AI SaaS market could reach $1.5 trillion by 2030, growing at a CAGR of 37.66%. Whether you're looking for your first career or your next career, our program will prepare you for these emerging job roles in AI and data analytics.

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At a Glance: Generative AI Data Analyst Training

  • Entry-Level Design: No prior AI or Data Analyst experience required.
  • Always Affordable: Explore budget-friendly tuition options.
  • 100% Online: Learn from anywhere with flexible online classes
  • Job Preparation: Learn critical skills for real-world data analyst roles.
  • Salary Potential: Unlock career paths with competitive salaries.
  • Hands-On Learning: Work on Generative AI projects.

Instructor-Led Lectures

Learn from seasoned professionals at the WorkForce Institute through engaging, interactive sessions in a vibrant virtual classroom.

Live, Project-Based Learning

Join small group sessions in WorkForce Institute's hands-on courses to work together and learn as a team

How Does a Generative AI Data Analyst Bootcamp Work?

A Generative AI Data Analyst Bootcamp teaches you how to use AI tools that analyze data, highlight insights, and improve data visualization end results. The program helps you prepare for AI-focused jobs and keeps your skills up to date as your industry changes.

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Virtual, Hands-On Assignments

Your courses include interactive lab assignments where you can practice what you learn in a virtual setting. These "sandbox" labs let you safely explore generative AI models, data tools, and machine learning techniques without affecting real systems. You'll gain practical experience that builds your skills and confidence for real-world applications.

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Comprehensive Student Support

We offer strong support to help you learn generative AI and data analysis skills on your timeline. You’ll have weekly access to virtual office hours, one-on-one mentoring, and a 24/7 AI tutor for help anytime. Our team is here to guide you every step of the way, connecting you with the resources you need as you learn.

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Dedicated Data Analyst Certification Preparation

Our bootcamp includes dedicated certification preparation (exam preparation, targeted reviews, and mock exams) during the final weeks of the program. We help students review and solidify skills prior to taking the industry-aligned Data Analyst Associate certification exam.

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Career Exploration

This bootcamp prepares learners of all backgrounds for an entry-level job in AI and data analytics. We’ll help you find internships where you can use your new skills in real-world settings. You’ll also provide you with access to a job platform with opportunities, a talent portal where employers can discover you, and expert advice on building a strong resume and portfolio.

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Capstone Project

Throughout the bootcamp, you’ll build a robust portfolio that showcases your skills with the latest AI tools and data analysis techniques. You’ll work on real-world datasets and generate insights using advanced AI models. The program includes a "Hands-on AI Challenge," where you’ll solve data-driven problems using generative AI technologies. At the end of the bootcamp, you'll complete two career simulations — projects designed to replicate the challenges you'll face in an AI Data Analyst role.

Career Services

Our career services provide support in three distinct ways:

  • Career coaching

    Achieve your career goals with 30-minute, one-on-one coaching sessions focused on personalized career strategies and growth.

  • Interview preparation

    Get ready for interviews with mock interview sessions tailored to the generative AI and data analytics space. Learn how to excel in both technical and behavioral interviews.

  • Resume Building

    Craft a standout IT resume and portfolio with the help of Workforce Institute’s career coaches, ensuring you highlight your AI skills and industry certifications effectively.

What Emerging Careers and Job Roles Can I Earn after Completing a Generative AI Data Analytics Bootcamp?

Our program prepares students with the skills needed for diverse AI data analyst roles. While job titles and salaries can differ, graduates can explore a wide range of career opportunities in the field.

Role Average Salary
AI Researcher
  • AI researchers focus on advancing the field of artificial intelligence by developing new algorithms, models, and technologies. Their work drives innovation in areas like natural language processing, computer vision, and machine learning
$58,000 - $78,000
AI Engineer
  • AI engineers design, develop, and deploy AI-based systems and solutions, combining programming expertise with advanced AI tools. They create applications like chatbots, recommendation engines, and predictive analytics platforms.
$105,000 - $140,000
Machine Learning Engineer
  • Machine learning engineers build and optimize machine learning models that enable systems to learn from data and improve over time. Their work supports applications like fraud detection, image recognition, and personalized recommendations.
$80,000 - $100,000
Robotics Engineer
  • Robotics engineers design and program intelligent robots that can perform tasks autonomously. They combine expertise in AI, mechanical engineering, and electronics to create innovative robotics solutions for industries like manufacturing and healthcare.
$103,000 - $156,000
Data Scientist
  • Data scientists analyze complex data to identify patterns, build predictive models, and solve business problems. They use AI and machine learning tools to extract insights and drive strategic decision-making in various industries.
$111,000 - $136,000

*All salary data sourced from salary.com

Free Career Assessment

    Is this the right career path for you? Take our free career assessment to determine which path is the best fit for you.

    Free Career Assessment

Imagine Your Career as an AI Data Analyst…

AI Data Analyst Certification: Unlock the Power of Data

As an AI Data Analyst, you’ll turn raw data into useful insights that your employer can use to improve sales, productivity, and operations. The data you uncover will help guide business decisions. Beyond the roles listed above, many career options focus on analyzing data, improving machine learning algorithms, and solving problems with AI technology.

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Program Details

  • The Generative AI Data Analyst program is ideal for students who are dedicated to full-time learning and ready to dive deep into this exciting field. You'll work on real-world projects, collaborate with peers, and receive personalized support from instructors and career services to help you transition into a career in generative AI.
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Price:

$6,000 ($5,500 with prepay discount!)

Length:

12 weeks

Weekly commitment:

10-15 hours

Weekly, instructor-led sessions teach you everything you’ll need to know about the intersection of generative AI and AI-led data analysis. You’ll reinforce newfound skills through hands-on labs, which offer a controlled learning environment where you can test theories, make mistakes, and solve problems. Work alongside peers to share ideas and learn from diverse perspectives.

What Will I Learn in a Generative AI Data Analyst Bootcamp?

Generative AI is rapidly automating data-related tasks. While these tasks can certainly enhance productivity, they can also threaten careers in data analysis, business intelligence, reporting, operations, and finance.

A generative AI bootcamp can future-proof your career by teaching you how to leverage AI tools to elevate your work, rather than replace it. By mastering skills in automation, deep learning, model tuning, and data collection, you position yourself as a valuable expert in generative AI to enhance analytics processes. This knowledge not only keeps you relevant; it also opens opportunities in emerging AI-centric roles, ensuring long-term career resilience.

Our curriculum teaches everything you need for a career in generative AI and data analysis. You’ll learn to use AI tools, work with data, and understand machine learning. Plus, you’ll complete real-world projects that show your ability to solve problems with AI-powered data analysis.

  • Best Cloud Certification Introduction to IT Fundamentals

    Module 1: Introduction to AI & Deep Learning

    Module provides a foundational understanding of artificial intelligence, its types, and how deep learning drives advanced AI technologies.
    • Overview of AI
      • Learn what artificial intelligence is and how it works.
    • Types of AI
      • Explore different types of AI, including narrow, general, and superintelligence.
    • AI in Data Analytics
      • Understand how AI is transforming the way data is analyzed and used for decision-making.
    • Basics of Deep Learning
      • Discover the foundations of deep learning and how it powers advanced AI models.
    • Learning vs. Deep Learning in AI
      • Compare traditional machine learning with deep learning to see how they differ.
    • Applications of AI
      • Examine real-world examples of AI in industries like healthcare, finance, and technology.
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    Module 2: Basic Data Analytics and Statistics

    Module introduces core statistical concepts and techniques essential for analyzing and interpreting data effectively.
    • Descriptive Statistics
      • Learn how to summarize and describe data using measures like mean, median, and standard deviation.
    • Probability and Data Distributions
      • Understand the basics of probability and common data distributions like normal and binomial.
    • Inferential Statistics
      • Explore techniques for making predictions and drawing conclusions from sample data.
    • Correlation and Causation
      • Discover how to analyze relationships between variables and differentiate correlation from causation.
    • Sampling Methods
      • Learn different sampling techniques to collect data that represents a population.
    • Data Cleaning Techniques
      • Gain skills to identify and fix errors or inconsistencies in datasets for accurate analysis.
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    Module 3: Introduction to Machine Learning

    Module provides an overview of key machine learning concepts, techniques, and algorithms used to create predictive models.
    • Supervised Learning
      • Learn how machines use labeled data to make predictions or classifications.
    • Unsupervised Learning
      • Explore techniques where machines find patterns in data without predefined labels.
    • Reinforcement Learning
      • Understand how machines learn to make decisions by interacting with an environment and receiving feedback.
    • Common ML Algorithms
      • Get familiar with widely used algorithms like linear regression, decision trees, and neural networks.
    • Bias-Variance Tradeoff
      • Discover how to balance model accuracy and generalization to prevent underfitting or overfitting.
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    Module 4: Data Collection and Preparation

    Module focuses on gathering, organizing, and refining data to ensure it’s ready for analysis and machine learning models.
    • Data Acquisition
      • Learn methods for collecting data from various sources like databases, APIs, and web scraping.
    • Data Formats and Structures
      • Understand common data formats like CSV, JSON, and how to organize data efficiently.
    • Data Preprocessing
      • Explore techniques to clean and transform raw data into a usable format for analysis.
    • Handling Missing Data
      • Discover strategies to address incomplete data, including imputation and removal methods.
    • Feature Engineering
      • Learn how to create and optimize features to improve model performance.
    • Data Splitting for ML
      • Understand how to divide data into training, validation, and test sets for building and evaluating models.
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    Module 5: Basics of Generative AI Models

    Module offers an introduction to the principles, types, and real-world applications of generative AI technologies.
    • Introduction to Generative AI
      • Learn how generative AI creates new data, such as images, text, and audio, by learning patterns from existing data.
    • Types of Generative Models
      • Explore key models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
    • Applications of Generative AI
      • Understand how generative AI is used in fields like content creation, data augmentation, and simulation.
    • Training Generative Models
      • Learn the process of training generative models, including data preparation and optimization techniques.
    • Challenges in Generative AI
      • Discover the limitations of generative AI, such as bias, ethical concerns, and computational requirements.
  • Best Cloud Certification Career Simulation 2

    Module 6: Data Exploration and Visualization

    Module teaches techniques to explore, analyze, and present data in a clear and impactful way.
    • Exploratory Data Analysis (EDA)
      • Learn how to examine datasets to uncover patterns, trends, and anomalies.
    • Visualization Techniques
      • Discover methods to represent data visually using charts, graphs, and plots.
    • Python Visualization Libraries
      • Gain hands-on experience with tools like Matplotlib, Seaborn, and Plotly for creating visualizations.
    • Advanced Data Visualization
      • Explore sophisticated visual techniques like heatmaps, scatter matrices, and 3D plots.
    • Insight Generation from Data
      • Learn to derive meaningful insights by interpreting visual data representations.
    • Storytelling with Data
      • Understand how to use data visualizations to craft compelling narratives that inform and persuade.
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    Module 7: AI Model Training and Evaluation

    Module covers the key steps and techniques for building, training, and assessing the performance of AI models.
    • Data Splitting and Model Training
      • Learn how to divide data into training and testing sets to build accurate models.
    • Loss Functions and Optimizers
      • Understand how loss functions measure errors and how optimizers adjust models to improve performance.
    • Training Process and Techniques
      • Explore effective methods for training AI models, including iterative and batch learning.
    • Model Evaluation Metrics
      • Discover metrics like accuracy, precision, and recall to evaluate model performance
    • Cross-Validation
      • Learn how cross-validation ensures model reliability by testing it on different data subsets.
    • Overfitting and Underfitting
      • Understand how to identify and fix issues where models perform poorly on new data.
  • Best Cloud Certification Career Simulation 3

    Module 8: Model Tuning and Optimization

    Module focuses on refining AI models to enhance their accuracy and performance.
    • Hyperparameter Tuning
      • Learn how to adjust model settings to achieve the best possible performance.
    • Regularization Techniques
      • Understand methods to prevent overfitting and improve model generalization.
    • Feature Selection Methods
      • Explore techniques to identify and use the most relevant features for your model.
    • Ensemble Learning Techniques
      • Discover how combining multiple models can improve predictions and reduce errors.
    • Model Selection and Comparison
      • Learn to compare different models and choose the one that works best for your data.
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Learn from Industry Experts

Our instructors are seasoned experts in Generative AI, equipped with years of experience in developing AI-powered solutions and innovative applications. With their guidance, you'll gain the knowledge and hands-on skills needed to create, optimize, and implement AI-driven content, automation, and decision-making systems that align with industry trends and best practices.

James Meredith

Generative AI Instructor

Ivy League-graduate Data Scientist, Software Developer, and experienced Data Analyst with a deep expertise in data acquisition, modeling, machine learning, and Python-based software development. Proficient in quantitative analyses across healthcare, business, and economics sectors. Committed to deriving actionable insights from data, optimizing evaluations, enhancing revenue growth, and delivering robust software solutions.

Muhammad Shoaib

Generative AI Instructor

Muhammad Shoaib is a dedicated professional with a strong background in data analytics and AI, specializing in creating innovative solutions that bridge the gap between technology and business needs. With experience in both teaching and hands-on project work, Muhammad has guided learners through key concepts like data collection, preparation, machine learning, and AI model development. His practical, real-world approach to instruction ensures students gain the technical expertise and problem-solving skills necessary to excel in the fast-evolving fields of AI and data science. Muhammad is passionate about empowering individuals to harness the power of AI to drive meaningful impact.

Prices and Payment options

Immersive Program Features

12 Weeks Program

Instructor-led Sessions

1:1 Career Sessions

Annual Course Access

Tuition Guarantee

Tuition Guarantee

We are confident our course will meet & exceed your expectations. However, if for any reason you are not satisfied within the first 15 days of your program, we will refund your tuition.

Upfront Payment

Get An Additional Discount Off Your Tuition When You Make A One-Time, Upfront Payment. 

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$6,000 To
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Generative AI Data Analyst Bootcamp FAQs

What is generative AI?

Generative AI is a type of artificial intelligence that creates new content, such as text, images, audio, or video, by learning patterns from existing data. It uses advanced models like GANs (Generative Adversarial Networks) and transformers to produce outputs that closely resemble human-created content.

You’ll learn how to use AI tools to analyze data, create predictive models, and generate actionable insights. The program also covers essential topics like machine learning, data visualization, and real-world applications of generative AI in various industries.

Our Bootcamps take 12 weeks to complete

Workforce Institute offers bootcamp programs for UI/UX Design, Digital Marketing, and Generative AI Data Analysis.

This bootcamp program takes 12 weeks to complete, and requires an estimated 10-15 hours per week.

Our program is designed to be manageable and flexible, requiring an average time commitment of just 10-15 hours per week over the course of 12 weeks. With this pace, you’ll be able to balance your learning with other commitments, making it easy to stay on track and achieve your goals.

Prerequisites for these modules often include a basic level of education, such as a high school diploma, and some relevant work experience, especially for leadership or technical tracks. Key prerequisites for tech-focused programs typically include familiarity with software tools like Microsoft Office or Google Suite, and for more specialized modules, proficiency in industry-specific software (e.g., data analytics tools, CRM platforms, or project management tools like Asana or Trello). You’ll also need reliable internet access to connect to our online program and attend live learning sessions.

Yes, we do! Our team of experienced career coaches is dedicated to supporting your professional journey every step of the way. From crafting a standout resume that highlights your unique skills and achievements, to conducting personalized mock interviews that prepare you for real-world scenarios, we’re here to help you build confidence and stand out to potential employers.

We also connect you with valuable internship and job opportunities, tailored to your career goals, and provide ongoing guidance throughout the application and interview process. Whether you're transitioning into a new industry, advancing in your current field, or exploring new career paths, our career coaches are committed to equipping you with the tools, insights, and support you need to succeed.