AI Developer

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CONSULTANCY SERVICES

AI Developer BOOTCAMP

Master the most sought-after skills in Artificial Intelligence development with expert-led, hands-on training that prepares you for real-world applications—empowering you to design intelligent solutions, lead innovation, and accelerate your career in today’s AI-powered world.

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START DATE

October 6th, 2025

Duration

16 Weeks

Format

Online
  • Why AI?

Build Your Future in AI

Artificial Intelligence is one of the fastest-growing and most transformative fields in today’s job market. According to the U.S. Bureau of Labor Statistics and recent industry forecasts, employment in AI-related occupations—such as machine learning engineers, AI developers, and data scientists—is projected to grow by 23% from 2025 to 2030, much faster than the average for all occupations. This rapid growth is fueled by the widespread adoption of AI across industries including healthcare, finance, education, robotics, and cybersecurity.

In 2025, AI roles offer highly competitive salaries. The average annual salary for an AI Developer is approximately $127,000, with experienced professionals and specialized roles like Machine Learning Engineers and AI Architects earning upwards of $160,000 or more per year, depending on skill level and location. This makes AI not only one of the most future-proof career paths, but also one of the most financially rewarding.

Now is the ideal time to launch your career in Artificial Intelligence. Our AI Developer Training Bootcamp is designed to equip you with the technical skills, hands-on experience, and career support needed to break into the field and thrive in an AI-driven future.

$111,681

The Average salary for a AI Developer in 2025

$175,262

The average salary for a AI Engineer in 2025

$112,590

The average salary for a Data Scientist in 2025

23%

What is the Projected Job Growth?

  • CURRICULUM

Hands-On Training for a Future-Proof Career

The AI Developer Bootcamp offered by TAB is designed to equip students with the essential skills to build intelligent systems and applications that solve real-world problems. This immersive program prepares participants to design, train, and deploy machine learning models, while developing a strong foundation in programming, data preprocessing, neural networks, natural language processing (NLP), and deep learning.

Students will explore key artificial intelligence concepts including supervised and unsupervised learning, model evaluation, computer vision, generative AI, and ethical AI development. Our hands-on, browser-based labs simulate real-world AI workflows—giving students the opportunity to work with tools like TensorFlow, PyTorch, scikit-learn, and popular cloud platforms to build and deploy AI models.

With over 200 hours of focused, project-based instruction, the bootcamp emphasizes practical experience, ensuring students gain not just theoretical knowledge, but job-ready skills. From building chatbots and recommendation engines to deploying AI in the cloud, participants complete portfolio-worthy projects to demonstrate their capabilities to employers.

Beyond technical training, the program includes a comprehensive career development track. Students receive 1-on-1 support for crafting competitive resumes, optimizing LinkedIn profiles, preparing for interviews, and building connections with AI professionals. The curriculum also helps prepare learners for recognized certifications in AI and machine learning.

This non-credit bootcamp can be completed in just 16 weeks, offering an efficient, intensive path to launching a high-growth career in artificial intelligence and machine learning.

  • CERTIFICATIONS

IBM AI Developer

IBM AI Developer Professional Certificate

IBM AI Developer Professional Certificate

The IBM AI Developer Professional Certificate is a training program designed to equip learners with the essential skills to build and deploy AI-powered applications. The certificate covers topics such as machine learning, deep learning, natural language processing, and AI model deployment using tools like Python, TensorFlow, PyTorch, and IBM Watson. Ideal for aspiring AI developers, the program includes hands-on projects to build real-world experience and prepare for careers in AI and machine learning.

Azure AI Engineer

Microsoft Certified: Azure AI Engineer Associate

Microsoft Certified: Azure AI Engineer Associate

The Microsoft Certified: Azure AI Engineer Associate certification validates the skills needed to build, manage, and deploy AI solutions using Microsoft Azure. Designed for professionals with experience in AI and data science, this certification focuses on using Azure Cognitive Services, Azure Machine Learning, and responsible AI practices. It is ideal for AI engineers who develop and integrate AI models into cloud-based applications. Candidates typically prepare for this certification by taking the AI-102 exam: Designing and Implementing an Azure AI Solution.

CCST - Cybersecurity

Cisco Certified Support Technician - Cybersecurity

Cisco Certified Support Technician - Cybersecurity

The Cisco CCST Cybersecurity certification validates an individual’s knowledge and skills in foundational cybersecurity concepts, such as security principles, network and endpoint security, vulnerability assessment, risk management, and incident response. It demonstrates their readiness for entry-level cybersecurity roles, such as Cybersecurity Technician or Tier 1 Help Desk Support.

CCST - Networking

Cisco Certified Support Technician - Networking

Cisco Certified Support Technician - Networking

The "CCST Networking" certification which stands for "Cisco Certified Support Technician - Networking," confirms an individual’s fundamental understanding of networking concepts. It demonstrates their ability to handle entry-level network support tasks such as troubleshooting common network issues, understanding network devices, and applying network protocols. This certification qualifies individuals for roles like Network Support Technician or Help Desk Specialist.

AI Developer Training Curriculum

Part I: Training Modules Breakdown

1. Foundations of AI & Python Programming
     a. Python for data science
     b. Object-oriented programming
     c. APIs and JSON
     d. Version control with Git/GitHub

2. Core Machine Learning Concepts
     a. Supervised vs unsupervised learning
     b. Model training, validation, and evaluation
     c. Data preprocessing & visualization
     d. Projects: Sentiment analysis, recommendation system

3. Deep Learning & Neural Networks
     a. Intro to TensorFlow and PyTorch
     b. Building and training neural networks
     c. Image recognition and natural language models

4. Generative AI & Large Language Models
     a. Working with OpenAI & Hugging Face APIs
     b. Prompt engineering
     c. Fine-tuning LLMs
     d. Real-world use cases (chatbots, smart content)

5. AI Developer Tools & Automation
     a. GitHub Copilot and Cursor AI for coding
     b. Using ChatGPT to automate code review and testing
     c. Deployment with Docker & cloud services
     d. Basic LangChain for building AI agents

1. Programming & DevOps
     a. Python, FastAPI, Flask
     b. Git, GitHub, GitHub Copilot
     c. Docker, VS Code, Cursor AI
     d. CI/CD pipelines

2. Machine Learning & AI
     a. scikit-learn, pandas, NumPy
     b. TensorFlow, Keras, PyTorch
     c. OpenAI (GPT APIs), Hugging Face Transformers
     d. LangChain, Pinecone, FAISS
     e. ChatGPT for development, research, testing, and automation

3. Data & Cloud
     a. SQL, MongoDB
     b. AWS/GCP/Azure (basics)
     c. Oracle VirtualBox (for local experimentation)

● AI Resume & LinkedIn optimization
● Interview coaching & whiteboard challenges
● Career tracks in AI: ML Engineer, Prompt Engineer, AI Developer
● Preparation for certifications:
     ○ TensorFlow Developer Certificate
     ○ Microsoft Azure AI Fundamentals

Project: Build an AI-powered clone of a social media platform like TikTok or Facebook.Students will work in small teams to design and deploy a web app that
uses AI for:

     1. Content Recommendations (e.g., video or post feed)
     2. Auto Tagging with NLP/vision models
     3. Toxic Comment Filtering using sentiment analysis
     4. Smart Reply Suggestions powered by GPT-4 or similar APIs

Deliverables:
     1. Live app demo and code presentation
     2. Full GitHub repository
     3. Project report + user documentation
     4. Resume-ready project portfolio entry

Scholarships are available

Contact us for a personalized consultation on your financing options, including partial scholarships, ISAs and Payment Plans.

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