Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. The objectives of this course are as follows:

➼ To provide basic technical skills for Deep Learning

➼ To learn and implement Deep Learning algorithms

➼ To introduce important application areas of Deep Learning such as Computer Vision, Natural Language Processing, Speech Analysis, Text Processing, Human Activity Analysis, etc.

➼ To impart necessary research and technical writing skills

➼ To implement end-to-end hands-on Deep Learning projects

➼ Strong theoretical foundation of the fundamental concepts by professors & researchers from IITs, IIITs, NITs, and other institutes of international repute. 

➼ Hands-on coding practice and project development in guidance of Industry experts, Research Scholars and Top-level programmers.

➼ Regular interaction, assignments, quizzes, and evaluations.

➼ Networking opportunity with participants reputed institutes and industries.

➼ Opportunity to work on end-to-end projects and assistance in resume, portfolio building.

➼ A chance to publish research papers and participate in international conferences.

➼ Continuous assistance during the course and after that, lifetime access to the learning material, including Slides, software, codes, and other resources.

➼ Historical perspective and evolution of Deep Learning.

➼ Introduction to deep Generative and Discriminative models. 

➼ Regularization: Bias Variance Trade off, L2 regularization, Dataset augmentation, Early stopping.

➼ Recent Trends in Deep Learning Architectures, Residual Networks, Fully connected CNN etc .

➼Training and optimizing deep networks.

➼Transfer learning for Computer Vision.

➼ Recurrent Neural Network (RNN) and Sequence to Sequence (Seq2Seq) learning.

 Fundamentals of Python Programming.

 ➼ Introduction to Computer Vision and its applications.

➼ Pre-trained language models (Transformers, BERT, GPT, etc).

By the end of this certification course, the participants should be able to:

➼ Possess essential programming skills for Deep Learning

➼ Understand the basic know-how about Deep Learning

➼ Understand a wide variety of Deep Learning & Deep Learning algorithms

➼ Understand how to pre-process the data and evaluate the models generated from data 

➼ Apply these algorithms to real-life problems, communicate their results in technical reports

Moreover, they will also acquire a course competition certificate on completing the assigned project. 

Sample Course Certificate: Coming soon...

  • Course Fee ₹24000   ₹12000
  • Course Duration 40+ hours
  • Register Before 2024-07-31
  • Eligibility Criteria ML Basics
  • Registration & Payment Click Here