Learn AI For Developers Online: Free Course with AI Tutor & Certificate
This ai developer course teaches you how to build intelligent applications in about 1 hours. You'll complete 73 video lessons covering generative AI, APIs, and MLOps. By the end, you'll be ready to deploy AI agents and integrate predictive models into your software.
What you'll learn in this AI For Developers course
Five concrete outcomes you'll walk away with, each mapped to modules in the curriculum below.
Develop and implement AI-powered applications using advanced machine learning and deep learning techniques.
Master the use of AI APIs, models, and tools to enhance coding productivity and integrate AI solutions into existing workflows.
Build and deploy AI agents and agentic workflows for real-world applications, leveraging platforms like LangChain and Amazon Bedrock.
Design and execute end-to-end MLOps processes for deploying and managing AI models in production environments.
Apply advanced prompt engineering and generative AI techniques to create innovative solutions and improve decision-making processes.
AI For Developers course syllabus
01 Module 1: AI Foundations for Developers
- Grasping the Fundamentals of Generative AI and LLMs
- Understanding What AI Is (and Isn't) for a Developer
- Applying Generative AI to Developer Workflows
- Exploring the Transformer Architecture
- Differentiating AI vs. Non-AI Solutions
- The Future of AI and the Path to AGI
02 Module 2: Applied Machine Learning and Deep Learning Intuition
- Machine Learning Fundamentals & The ML Process
- Supervised Learning Part 1: Linear & Logistic Regression
- Supervised Learning Part 2: Decision Trees, KNN, and SVM
- Unsupervised Learning: K-Means Clustering & Image Compression
- Reinforcement Learning: Markov Decision Process & Q-Learning
- Deep Learning Part 1: Perceptrons & Backpropagation Theory
- Deep Learning Part 2: RNN, CNN & Practical Stock Prediction Demo
- Natural Language Processing (NLP) & Sentiment Analysis
03 Module 3: Mastering Generative AI and LLMs
- Understanding Tokens: The Building Blocks of LLMs
- Understanding Prompt Engineering and Its Challenges
- Core Techniques for Effective Prompt Engineering
- Advanced Prompting Techniques
- Implementing Semantic Search with Text Embeddings
- Understanding Retrieval Augmented Generation (RAG)
- Building a RAG Pipeline with LlamaIndex
- Decision Making: Prompting vs. RAG vs. Fine-Tuning
- Building a YouTube Chatbot with LangChain
04 Module 4: Working with AI APIs, Models, and Tools
- Getting Started with Amazon Bedrock
- Integrating Foundation Models into Python Code
- Calling Bedrock Models with the AWS SDK
- Choosing the Right Foundation Model for Your Use Case
- Getting Started with Amazon Q Developer in VS Code
- Boosting Coding Productivity with Amazon Q
- A Developer's Guide to Hugging Face Transformers
- Building with the LangChain Framework
05 Module 5: Building AI Agents and Agentic Workflows
- Conceptualizing AI Agents: How They Actually Work
- Building an End-to-End AI Agent in LangChain - 1
- Building an End-to-End AI Agent in LangChain - 2
- Enabling Tool Use and Function Calling with Amazon Bedrock
- Understanding and Enabling Long-Term Memory in Bedrock Agents
- Implementing Agent Memory Programmatically with Python
- Building a Computer-Use Agent with NVIDIA Nemotron
- Deploying AI Agents to Production with AgentCore
- Getting Started with OpenAI Agents SDK
- Advanced Agentic Patterns and Workflows
- Introduction to the Model Context Protocol (MCP)
- Integrating MCP Tools with Strands Agents
06 Module 6: Building and Integrating AI-Powered Applications
- Build a Full-Stack Serverless Web App (Workshop Part 1)
- Building the Real-Time Backend with Lambda and SNS
- Integrating the Frontend and Exploring Pub/Sub with IoT Core
- Process Images Asynchronously with Lambda and S3 (Workshop Part 3)
- Analyze User Data with Kinesis and QuickSight (Workshop Part 4)
- Introduction to Event-Based Architectures with EventBridge
- Publishing Events and Creating a CloudWatch Metrics Dashboard
- Enriching Events and Routing Maintenance Alerts with SNS
- Build a Full-Stack AI App with Amplify AI Kit
- Create a Game Prototype with Prompt Engineering
07 Module 7: Production, Deployment, and MLOps
- Understanding the Generative AI Application Lifecycle (LLMOps)
- Workshop: End-to-End MLOps with Amazon SageMaker
- Deploying Generative AI in Production with NVIDIA NIM
- Workshop: Deploying Machine Learning Models for Inference
- Building Safe and Ethical AI with Amazon Bedrock Guardrails
- Securing Generative AI Applications
- Workshop: Automating ML Workflows with SageMaker
- Workshop: Distributed ML Training with PyTorch and SageMaker
- Workshop: Training and Deploying Models with Kubeflow and SageMaker
- Workshop: Building and Operationalizing Hugging Face Models on SageMaker
- Workshop: Building a RAG Application in Minutes
- Workshop: Setting Up a RAG Demo on NVIDIA AI Workbench
08 Module 8: Advanced Topics and Real-World Case Studies
- Case Study: AI Agents for AWS Cost Prediction
- Case Study: ServiceNow's Approach to Document Intelligence
- Case Study: Transforming Digital Banking with AI Contact Centers
- Case Study: GenAI-Powered Cloud Security Remediation
- Case Study: Real-Time Voice Transcription for Finance
- Understanding the Carbon Footprint of Transformer Models
- Workshop: Federated XGBoost with NVIDIA FLARE
- Workshop: Building a Full AI Course in 10 Hours
Real-world projects you'll work on
Practice the exact kind of work AI For Developers professionals do on the job.
Developing a Personalized AI-Powered Shopping Assistant for Amazon
Creating a Real-Time AI-Driven Customer Support Chatbot for Google
Building a Predictive Analytics Platform for Tesla's Autonomous Vehicles
Designing a Sentiment Analysis Tool for Facebook's Social Media Insights
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this AI For Developers course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- Software developers in India looking to integrate AI features into their applications.
- Backend engineers wanting to master MLOps and deploy machine learning models.
- Computer science students aiming to build a portfolio with generative AI projects.
- Tech professionals transitioning into specialized AI engineering roles.
Prerequisites
- Basic understanding of programming logic and software development is required.
- Familiarity with Python or a similar backend language is highly recommended.
- No prior machine learning experience is needed to start the foundation modules.
How learning works on LearnTube
The structure of a bootcamp, the price of free.
AI curates your path
Our AI picks the top 1% of video content for each topic and arranges it into a structured, goal-based curriculum. No more tutorial roulette.
Learn, then get quizzed
After every lesson, your AI tutor asks you a question and gives personalised feedback on your answer, so gaps get fixed immediately.
Finish with proof
Complete the course, build the capstone project, and claim a certificate recognised by 900+ hiring partners.
A complete AI For Developers course: free, structured and job-focused
You'll learn to build an AI-powered shopping assistant for Amazon right from the start. This ai engineering course online zooms out to cover the complete lifecycle of intelligent software creation. Over 8 modules, you'll progress from Grasping the Fundamentals of Generative AI and LLMs to mastering Applied Machine Learning and Deep Learning Intuition. We cover exactly what modern engineers need, including Working with AI APIs, Models, and Tools to enhance your existing codebase.
The curriculum gets highly practical as you advance. You'll tackle Building AI Agents and Agentic Workflows, followed by Building and Integrating AI-Powered Applications. You'll also complete hands-on projects like creating a real-time AI-driven customer support chatbot for Google and a predictive analytics platform for Tesla's autonomous vehicles. Finally, the training wraps up with Production, Deployment, and MLOps, ensuring you can actually ship the models you build.
LearnTube makes this ai coding course entirely free to learn. We curate top YouTube video lessons and pair them with an AI tutor that quizzes you after every single video. This active testing ensures you actually retain the prompt engineering concepts. If you want to verify your new skills, you can opt for a paid certificate upon finishing the 73 lessons.
Jobs you can target after learning AI For Developers
AI For Developers is a gateway skill for some of the fastest-growing roles in tech.
Integrates machine learning models and AI APIs into software applications.
Manages the deployment, scaling, and monitoring of AI models in production.
Designs end-to-end intelligent systems and agentic workflows for businesses.
Typical entry-level salary ranges in India as of October 2026. Actual compensation varies by city, company and experience.
Earn a AI For Developers certificate employers recognise
Finish the course and claim a certificate you can share anywhere.
- Learn 100% free: every lesson, quiz and the AI tutor cost nothing
- Claim your certificate when you complete the course (an optional paid add-on)
- Recognised by 900+ hiring partners across India
- One click to share on LinkedIn and add to your resume
Why learners choose LearnTube
Real reviews from Google. You learn free, you get assessed free, and you pay only if you want the certificate.
Though I have 11 years of experience as an HRBP, the course helped me refresh my knowledge and gave me insights into new trends in the market. The modules were clear and easy to understand, and the quizzes were well designed. I have added the certificate to my LinkedIn profile.
I had a lot of doubts while learning, but the AI chatbot answered them in detail with simple summaries. The videos on the platform saved me a lot of time as I didn't have to search YouTube and watch random content.
Just earned my certificate in HR Management from LearnTube.ai! The platform is user-friendly and the assessment was a great way to validate my knowledge. Feeling proud of this accomplishment!
I enrolled in a LearnTube personalized course to get into a Data Analytics role. It helped me learn SQL in depth and gave me hands-on experience with Power BI. I attached the LearnTube certificate to my CV, it added credibility to my profile, and I'm currently in the interview process.
The interface is user-friendly and intuitive, making it easy to navigate the course. I encountered no errors during my time using the platform, which was a refreshing change from other online learning platforms.
Just cleared the Business Analyst assessment and got certified! Loved how the course simplifies big concepts like data-driven decision making into short, practical lessons. The automated quizzes kept me on track the whole time. Perfect boost for my resume!
The certificate gave me a real edge during my B.Tech. By the time I graduated, I had skills that set me apart from my peers, and the certification opened up more job opportunities. It gave me the confidence to stand out during interviews.
I manage many software projects as a General Manager and was looking for a good certification program to stay competitive. After researching many programs, I chose LearnTube and it was much better than I expected. The material is well-organized and practical, and what I liked most is the lifetime access.
Frequently asked questions
Everything learners ask before starting this AI For Developers course.
Do I get a certificate for this ai application development course?
Yes. You can purchase an optional certificate after completing all 8 modules and passing the AI quizzes. It verifies your ability to build and deploy generative AI applications.
Why not just watch regular YouTube videos?
LearnTube organizes scattered videos into a structured ai software development course. You also get an AI tutor that quizzes you after every single lesson, ensuring you actually understand concepts like deep learning intuition.
What software do I need for this ai developer course?
You'll need a code editor like VS Code and a Python environment installed. We also recommend setting up free accounts for LangChain and Amazon Bedrock to complete the hands-on API projects.
Do I need machine learning experience before starting?
No. While you should know basic programming, this ai coding course starts from scratch with AI Foundations for Developers. You'll gradually move into complex topics like agentic workflows and MLOps.
How long does this ai programming course take?
It takes about 1 hours to finish all 73 video lessons. Since it is entirely self-paced, you can complete the projects and modules on your own schedule without strict deadlines.
Is this generative ai for developers course free?
Yes. All video lessons, hands-on projects, and AI tutor quizzes are completely free. You only pay if you decide to add the optional verified certificate at the end of your training.
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