Course , Free Course ,

Deep Learning Fundamentals Course

Master deep learning concepts and models. Learn to implement deep learning algorithms and prepare for a career as a Deep Learning Engineer.

This course is designed for beginners who are interested in deep learning, Deep learning has received a lot of interest in part because it circumvents the constraints of conventional machine learning. The first drawback is that high-dimensional data cannot be handled by typical machine learning. As a result, as the volume of data grows, the performance of the conventional machine-learning model tends to plateau.

What will you learn Deep Learning Fundamentals Course?

  1. Industry Applications of deep learning
  2. Various examples in daily life with deep learning
  3. Artifical Neural Network Overview
  4. The Neuron
  5. How neuron works
  6. Hidden layer
  7. Activation Function
  8. Optimizer
  9. Loss Function
  10. Gradient Descent
  11. Stochastic Gradient Descent
  12. Backpropagation
  13. What is Perceptrons and overview
  14. Drop Out
  15. Basics and properties
  16. Gradient descent in once dimension
  17. Multivariate Gradient descent
  18. Gradient descent update
  19. Dynamic learning rate
  20. Adagrad
  21. RMSProps
  22. Adam
  23. Steps for creating model with Keras
  24. Steps for creating model with TensorFlow
  25. Convolutional layer
  26. CNN Architecture
  27. Invariance
  28. Convolutions
  29. The cross correlation operation
  30. Learning a kernel
  31. Feature map and receptive field
  32. Padding
  33. Stride
  34. Relu
  35. Maximum pooling and average pooling
  36. Flattening of layer
  37. Fully connected layer
  38. Idea behind RNN
  39. Applications of RNN
  40. One Hot Encoding
  41. Initialize model parameter
  42. Gradient Clipping
  43. Analysis of gradient in RNN
  44. Backpropagation in time in details
  45. GRU
  46. LSTMs
  47. Deep Recurrent neural Networks


Basic understanding of Python is required.


A warm welcome to Deep Learning Fundamentals Course.

The Deep Learnings market size is estimated to be worth $18.16 billion by end of 2023. That means the market is growing at a rapid rate of 41 percent from 2018 to 2023. Deep learning is getting used in all sectors – healthcare, fintech, e-commerce. As per Glassdoor the average salary of Deep learnings engineer is $136K.

This course is curated by industry AI experts and aligned with the need of the industry. You will master deep learnings concepts and will learn popular algorithms like CNN, RCNN, RNN, LSTM, RBM. You will build models using Keras and TensorFlow frameworks and implement deep learnings algorithms. This course will prepare you for a career as Deep Learnings Engineer.

By the end of this course, you will get the necessary knowledge required to enhance your career as Deep learnings engineer.
This course will help you boost your career in the booming Artificial Intelligence domain. So, start your AI journey today. We will see you in the course.

Who is this course for?

1. College Freshers
2. Anyone who is willing to learn Deep learning in simple and easy steps

Course Content

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Course Includes

  • 7 Lessons
  • 73 Topics
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