Applied Ai Program
Unlock the power of applied AI with this hands-on, end-to-end course designed for beginners and advancing professionals alike. Whether you're looking to build scalable ML pipelines or craft GenAI applications with Amazon Bedrock, this course delivers a practical learning journey grounded in real-world software development and data engineering workflows.
Who Should Enroll?
This course is ideal for:
- Software developers and data engineers transitioning into AI/ML roles.
- Aspiring ML practitioners seeking real-world project experience.
- Technical professionals interested in AWS SageMaker and Bedrock.
- Teams deploying scalable machine learning or generative AI solutions.
No prior AI/ML experience is required—just a solid grasp of programming basics and a willingness to learn by doing.
What You'll Learn
Through carefully structured modules, you'll gain applied expertise in:
- Navigating the AWS AI/ML ecosystem (SageMaker, Bedrock, Comprehend, Rekognition).
- Preparing, transforming, and managing data using Feature Store and S3.
- Training, tuning, and optimizing ML models with built-in and custom algorithms.
- Deploying and monitoring real-time and batch ML endpoints.
- Engineering prompts and building GenAI applications with Claude, Titan, and Llama.
- Architecting and deploying full-stack ML/GenAI solutions using AWS services
Learning Outcomes
By the end of this course, you will be able to:
- Set up a secure and scalable ML environment using IAM and SageMaker.
- Develop and deploy supervised learning models with hyperparameter tuning.
- Automate ML workflows using SageMaker Pipelines and CodePipeline.
- Build and monitor real-time AI services using API Gateway, Lambda, and Model Monitor.
- Leverage Amazon Bedrock to create GenAI solutions for summarization, Q&A, and chatbots.
Real-World Projects Include
Gain job-ready experience with guided projects such as:
- Churn Prediction Model using SageMaker built-in algorithms
- Fraud Detection Pipeline with hyperparameter optimization
- Real-Time Prediction Service with monitoring and version control
- Document Summarizer powered by Amazon Bedrock
- Internal FAQ Bot using Bedrock + S3
- Customer Review Analyzer with NER and sentiment analysis
Course Curriculum
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AWS AI stack: SageMaker, Bedrock, Comprehend, Rekognition
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IAM roles and permissions for ML
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AWS setup, IAM roles, S3 buckets for SageMaker
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SageMaker Studio & Notebooks
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Built-in algorithms and training workflows
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Inference endpoints & pipelines
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Train and deploy a classification model (e.g., churn prediction)
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Data import from S3
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Feature Store & Processing Jobs
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Data transformation pipeline with SageMaker
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Custom model training (e.g., XGBoost, sklearn)
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Hyperparameter tuning & optimization
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Spot training for cost savings
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Optimized pipeline for fraud detection or forecasting
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Real-time vs batch deployment
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Versioning & updates
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Monitoring with Model Monitor (drift, bias)
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Deploy & monitor a real-time prediction service
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What is Bedrock?
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Supported FMs: Claude, Titan, Jurassic, Llama
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When to use Bedrock vs SageMaker
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Summarization, text generation, Q&A using Bedrock
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Prompt engineering fundamentals
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Using Bedrock via AWS SDK / LangChain
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Optional: Fine-tuning via SageMaker JumpStart
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Internal FAQ Bot or document summarizer
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Architecting real-world ML/GenAI apps (API Gateway, Lambda, S3)
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CI/CD with SageMaker Pipelines / CodePipeline
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End-to-end deployment of chatbot or predictive API
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Internal FAQ Bot using Bedrock + S3
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Customer Churn Prediction with SageMaker
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Sales Forecasting API using SageMaker Pipelines
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Document Summarizer with Bedrock
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Product Review Analyzer (NER + sentiment using SageMaker + Bedrock)
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Amazon SageMaker Studio, JumpStart, Model Monitor, Pipelines
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Amazon Bedrock: Claude, Titan, Llama 2, Jurassic
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AWS SDK (Boto3)
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S3, IAM, Lambda, API Gateway, CloudWatch
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LangChain (optional GenAI integration)
Jonathan Campbell
- 72 Videos
- 102 Lectures
- Exp. 4 Year
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*MIN 5 COMPANY WALK-INS
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- Resume & Linkedin Building
- 1-1 Mock Interviews
- 100% Hands-on
- Certification
Tools Covered
You'll gain hands-on experience with leading AWS tools and services:
Amazon SageMaker
SageMaker Studio
SageMaker Pipelines
Model Monitor
JumpStart
Amazon Bedrock
Claude
Titan
Jurassic
Llama 2
AWS IAM
Amazon S3
Lambda
CloudWatch
Boto3
LangChain
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