Course Content
1. Artificial Neural Networks (ANN)

•  Single Layer Perceptron

•  MultiLayer Perceptron

•  Activation Functions (Linear, Sigmoid, Tanh, Relu, Leaky Relu)

•  Loss Functions

•  Optimization Techniques (Gradient Descent, Stochastic Gradient Descent, Mini Batch Gradient Descent, ADAM, RMSProp, AdaGrad, Nadam)

2. Convolutional Neural Network (CNN)

•  Conv Operations

•  Fully Connected Network

•  LeNet, AlexNet, ResNet, VGG

•  RCNN, Fast RCNN, Faster RCNN, Mask RCNN

•  YOLO, SSD

3. Recurrent Neural Network (RNN)

•  LSTM

•  GRU

•  CNN + RNN

•  Bi-Directional RNN

4. Generative Modelling (Unsupervised Learning)

•   Boltzmann Machine Deep Boltzmann Machine Restricted Boltzmann Machine

•   Deep Boltzmann Machine

•   Restricted Boltzmann Machine

•   AutoEncoders Standard AutoEncoders Variational AutoEncoders Stacked AutoEncoders

•   Standard AutoEncoders

•   Variational AutoEncoders

•   Stacked AutoEncoders

•   Deep Belief Networks

•   GAN

5. Deep Dream (Neural Style Transfer)

•  Deep Dream (Neural Style Transfer)

6. Reinforcement Learning

•  Reinforcement Learning

7. OpenAI

•  OpenAI

8. Gym

•  Gym

COURSE OVERVIEW

Deep learning is a subfield of machine learning that focuses on the development and application of artificial neural networks. It involves training deep neural networks with multiple layers to learn and make predictions from large amounts of data.

Deep learning has gained significant attention and popularity due to its ability to solve complex problems and achieve state-of-the-art performance in various domains such as computer vision, natural language processing, speech recognition, and more.

COURSE OBJECTIVES

Develop a solid understanding of the Unity game development engine and its core features.

Learn to create interactive and visually appealing games using Unity's tools and components.

Gain proficiency in game physics, scripting, and implementing game mechanics.

Understand the process of designing game levels and user interfaces for optimal player experience.

Course Instructors
Instructor 1

Ravikant Tyagi

Hello everyone, I am Ravikant Tyagi and I do have experience of 8+ years in IT as a developer and trainer. I have more than 100 websites live on internet and I have taught thousands of students, teachers & developers to learn to code and how to become professional developer with 100% practical knowledge.

Instructor 1

Aditya Singh

Teaching Assistant having a total of 6 months of experience in teaching IT professionals. So far I have successfully deliverd 15+ trainings at various tech companies/colleges

What People Says About us


Frequently Asked Questions
Can I attend a demo session before enrolment?

•  Yes! You can attend a One Demo class free of Cost.

What if I miss a class?

•  All Classes sessions are recorded in HD Quality , so if you miss a class so you can watch the recordings.

Will I get placement assistance?

•  100 % Placement Assistance.

Who are the Trainers at Brain Mentors?

•  All our Trainers are Software Professionals, Having 7 to 15 Years’ of Experience. All Trainers worked with Top Brands.

What if I have more queries?

•  Feel free to contact us on :7042434524 01145138947

Join Us Today

Questions, concerns or feedback? We're here to listen. Use the form to contact us.
image