Programme Parameters
Advanced Postgrad
10 Weeks (100 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
The Advanced AI and Machine Learning for Professionals course is designed for individuals in AI and data science roles looking to deepen their expertise. Over 10 weeks, participants will explore advanced topics such as deep learning, reinforcement learning, and computer vision. Across 10 Weeks, you will build practical fluency in deep learning and reinforcement learning, 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
The Advanced AI and Machine Learning for Professionals course is designed for individuals in AI and data science roles looking to deepen their expertise. Over 10 weeks, participants will explore advanced topics such as deep learning, reinforcement learning, and computer vision.
📋 Course Objectives
1. Gain working command of deep learning.
2. Develop hands-on skill in reinforcement learning.
3. Put biotechnology techniques to work on real datasets and case studies.
4. 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 deep learning
🚀 Key Learning Outcomes
• Confidence to implement deep learning in real projects.
• Confidence to reason about reinforcement learning in real projects.
• Tangible, reproducible biotechnology work to show supervisors or employers.
• 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
Advanced Machine Learning Techniques (3 Weeks)
Overview of advanced algorithms • Ensemble methods: boosting, bagging, stacking • Dimensionality reduction (PCA, LDA) • Time series forecasting models
Deep Learning Specialization (3 Weeks)
Deep learning basics: neural networks, activation functions • Architectures: CNNs, RNNs • Hyperparameter tuning and optimization • Transfer learning with pre-trained models
Reinforcement Learning (2 Weeks)
Introduction to reinforcement learning (RL) • Markov decision processes (MDPs), policies, and rewards • Deep Q-networks (DQN) and policy gradients • Applications: robotics, gaming, autonomous systems
Computer Vision and Image Processing (2 Weeks)
Fundamentals of computer vision • Feature extraction and object detection • Working with OpenCV and deep learning • Image segmentation, face recognition
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | Keras |
| Covered Tool / Platform | Pandas |
| Covered Tool / Platform | NumPy |
| Covered Tool / Platform | Matplotlib |
| Covered Tool / Platform | XGBoost |
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