Event Details
Online Certificate Program in “Deep Learning” (2Hrs/Day for 15 days)
ICFOSS is organizing an Online Certificate program in “Deep Learning”. This program runs from 17th February to 7th March 2025, to enable the participants to critically evaluate and adapt deep learning methods to new challenges and domains.
Objectives:
This course typically includes providing a comprehensive understanding of neural networks and their architectures, equipping participants with the skills to design and train deep learning models for various tasks such as image classifications. Additionally, it seeks to familiarize learners with cutting-edge research in the field and prepare them to apply deep learning algorithms to real-world problems. This program spans 15 days (2Hrs/Day/Online- Except holidays).
Participants will acquire dedicated live online support from experienced mentors at ICFOSS, ensuring comprehensive guidance throughout the program. Progress will be evaluated through assignments, simulation test and project.
Course Highlights:
|
Online learning |
Live Virtual Classroom |
|
Assignments & Simulation Test |
Custom learning path |
|
Project |
Certification |
Duration:
30 hours of Industry-Lead Training (2Hrs/Day for 15 days-Except holidays )
Syllabus |
||
Days |
Topics |
Details |
Day 1 |
Introduction to Deep Learning |
History, importance, differences between ML and DL, applications, overview of neural networks |
Day 2 |
Artificial Neural Networks (ANNs) Basics |
Neuron structure, activation functions (sigmoid, tanh, ReLU), forward and backward propagation |
Day 3 |
Training Neural Networks |
Loss functions, optimization techniques (Gradient Descent, Adam), overfitting and regularization |
Day 4 |
Deep Learning Frameworks |
Introduction to TensorFlow and PyTorch, building and training basic neural networks |
Day 5 |
Convolutional Neural Networks (CNNs) |
CNN architecture, convolution and pooling layers, use cases (image classification) |
Day 6 |
Hands-on with CNNs |
Building and training CNNs using TensorFlow and PyTorch |
Day 7 |
Recurrent Neural Networks (RNNs) |
RNN architecture, challenges (e.g., vanishing gradients), and applications in sequence data |
Day 8 |
Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) |
Detailed study of LSTM and GRU architectures, their advantages over standard RNNs, and practical use cases |
Day 9 |
Sequence-to-Sequence (seq2seq) Models |
Introduction to seq2seq models, encoder-decoder architecture, and applications in tasks like machine translation |
Day 10 |
Attention Mechanisms in seq2seq Models |
Incorporating attention mechanisms into seq2seq models to improve performance on long sequences |
Day 11 |
Transformer Models |
Understanding the Transformer architecture, self-attention mechanisms, and their evolution from RNN-based models |
Day 12 |
Natural Language Processing (NLP) with Transformers |
Applications of Transformers in NLP tasks such as language modeling, translation, and text generation |
Day 13 |
Advanced Transformer Architectures |
Exploring models like BERT, GPT, and T5, and their contributions to NLP advancements |
Day 14 |
Transfer Learning and Fine-Tuning |
Utilizing pre-trained models, fine-tuning techniques, and applications in various domains |
Day 15 |
Deployment and Future Trends |
Methods for deploying deep learning models, emerging trends like agentic AI and synthetic data generation |
Online Examination and Project Presentation
Target Audience:
Students, Faculty, Professionals and Others, in the field of Science and Engineering.
The number of participants for the proposed program is limited to 50 nos per batch.
Certification Criteria: Certification will be issued to participants who qualifies with:
80% of attendance
50% marks in Online Examination
50% marks in Assignments
50% marks on Project
Prerequisities: Proficiency in programming languages such as Python is essential for implementing algorithms and working with deep learning frameworks as Deep Learning course typically include a strong foundation in linear algebra, calculus, and probability theory.
Dates:
Training program |
Dates |
Time |
Registration Fee |
|---|---|---|---|
Online Certificate Program in Deep Learning |
17th February to 7th March 2025 |
6.00 PM to 8.00 PM |
Rs. 3,000 |
Registration Fee: Rs. 3,000 /-
For online payment, the bank accounts details of ICFOSS is as follows:
Account Name |
ICFOSS |
Account Number |
67242303296 |
IFSC |
SBIN0070737 |
Name of Bank |
State Bank of India |
Branch |
Technopark, Thejaswini, Thiruvananthapuram |
Application Deadline: 13th February 2025
Registration Link: https://applications.icfoss.org/online-dl/
For more details of the program, please contact +91 7356610110 | +91 2700012 /13 |+91 471 2413013 | +91 9400225962 | between 10:00-17:00 hrs for any clarifications.