Course Objective
Prepare students to use the integration of Embedded Systems and Artificial Intelligence to resolve challenges in industrial systems. Students will learn how incorporating machine learning and deep learning algorithms with embedded systems can streamline processes and automate tasks. Focus will be on developing system approach through integrated projects to master specific methods and tools applied in the aeronautics, space, automobiles, and multimedia domains. The course will impart an in-depth knowledge focussing on both theoretical and practical aspects.
Fee Structure
The course comprises of 6 modules mentioned under the Course Syllabus below. Student can enrol for the full course (6 modules) or is free to enrol for individual modules.
Registration Fee: Rs.500/-
Full Course Fees: Rs.94500/-
Each Module Course Fees: Rs.17500/-
Registration fees and course fees
should to be paid online or by Demand Draft.
Online Payment Details: Account Name – ICIT PVT LTD
Account Number: 27205000514
IFSC Code: SCBL0036107
Bank: Standard Chartered Bank
Bank Branch: Aundh Branch, 163, Harsh Orchid, New DP Road, Nagras RoadMall, Ward no 8, Aundh, Pune 411007
Demand Draft: To be drawn on any nationalized bank in favour of “ICIT Pvt. Ltd., Pune” and should
be payable at par.
Note that registration and course fees once paid are non refundable.
Deep Neural Network
- Introduction to Neural Networks
- Feedforward Neural Networks
- Backpropagation
- Activation Functions
- Loss Functions
- Optimization Algorithms
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Long Short-Term Memory Networks (LSTMs)
- Autoencoders
- Generative Adversarial Networks (GANs)
- Deep Reinforcement Learning
- Transfer Learning
- Neural Network Regularization Techniques
- Hyperparameter Tuning
Data Visualization using Tableau
- Introduction to Tableau
- Tableau Interface and Features
- Connecting to Data Sources
- Data Preprocessing in Tableau
- Creating Basic Charts (Bar, Line, Pie)
- Advanced Chart Types (Heat Maps, Tree Maps, Scatter Plots)
- Dashboard Creation
- Interactive Dashboards
- Using Filters, Groups, and Sets
- Calculated Fields and Table Calculations
- Parameters
- Data Blending
Fundamentals of Cloud Computing
- Introduction to Cloud Computing
- Cloud Service Models (IaaS, PaaS, SaaS)
- Cloud Deployment Models (Public, Private, Hybrid)
- Virtualization Basics
- Cloud Infrastructure Components
- Cloud Security Principles
- Networking in the Cloud
- Storage Options in the Cloud
- Identity and Access Management (IAM)
- Cloud Migration Strategies
- Monitoring and Management in the Cloud
Generative AI and Prompt Engineering
- Introduction to Generative AI
- Basics of Natural Language Processing (NLP)
- Introduction to Prompt Engineering
- Pretrained Language Models (such as GPT, BERT)
- Text Generation Techniques
- Fine-Tuning Language Models
- Conditional Generation
- Unconditional Generation
- Sampling Strategies
- Diversity and Control in Generation
- Bias and Fairness in Generative AI
