Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
This course provides an in-depth exploration of AWS’s powerful cloud computing services tailored for artificial intelligence, including machine learning, deep learning, data management, and processing services. Across 4 Weeks, you will work hands-on with machine learning, deep learning, and data management, then consolidate everything in a capstone project. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This course provides an in-depth exploration of AWS’s powerful cloud computing services tailored for artificial intelligence, including machine learning, deep learning, data management, and processing services.
📋 Course Objectives
1. Build practical fluency in machine learning.
2. Gain working command of deep learning.
3. Develop hands-on skill in data management.
4. Put biotechnology techniques to work on real datasets and case studies.
5. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in biotechnology
• R&D engineers and working professionals applying biotechnology in industry
• Academics and educators building research or teaching capacity in biotechnology
• Data and computational scientists moving into machine learning
🚀 Key Learning Outcomes
• Confidence to implement machine learning in real projects.
• Confidence to reason about deep learning in real projects.
• Confidence to apply data management in real projects.
• A demonstrable biotechnology project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to AWS and AI Services
Exploring the basics of AWS’s architecture and its comprehensive AI services.
AWS Machine Learning Services
Gaining detailed insights into using SageMaker, Comprehend, and Rekognition for practical AI applications.
AWS for Deep Learning
Utilizing AWS Deep Learning AMIs and containers, TensorFlow, and PyTorch integration.
Data Management and Processing in AWS
Building AWS data lakes, using AWS Kinesis for real-time data streaming and analytics.
Scalability and Cost Management
Developing strategies for managing scalability and optimizing costs in AWS.
Security and Compliance
Ensuring robust security measures and understanding AWS’s compliance frameworks.
Project and Capstone
Completing a comprehensive project from design to implementation using AWS to solve real-world AI challenges.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | SageMaker |
| Covered Tool / Platform | Comprehend |
| Covered Tool / Platform | Rekognition |
| Covered Tool / Platform | Deep Learning AMIs |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | PyTorch |
Frequently Asked Questions
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