Best and Free Deep Learning Course Online

A couple of decade ago, it was a luxury to have a mobile phone in our pocket. But today it has become a necessity. Since the first lockdown due to COVID-19, we are highly dependent on our mobile phones and laptops/PC to engage in work from home activities. Now-a-days, machines have become so advanced that they are taking over human beings in many fields. From recommendations appearing on our YouTube channel to dreaming of autopilot cars running on roads in nearby future, there is a growth in the brain of machines. That’s right! Machines with brain. A brain as good as or even better than human mind. It can detect what humans cannot sense.

The rapidly growing field called deep learning has unknowingly become a big part of our life. This field is the future of mankind. That’s why INFO4EEE is starting a Course on Deep Learning, a subject which will become a part of every human’s life, a field with uncountable Career Opportunities in coming future.

The topics which we are going to cover in deep learning series are given below:

Syllabus

1. Fundamentals of Artificial Intelligence
1. Definition of AI
2. Need of AI
3. History of AI
4. Is it similar to Human Intelligence?
5. Types of AI
6. Applications of AI
2. Fundamentals of Machine Learning
1. Definition of Machine Learning
2. Need of Machine Learning
3. Pre-requisites of Machine Learning
4. Implementation of Machine Learning
5. Supervised Learning and Unsupervised Learning
6. Classification in Machine Learning Algorithms - Neural Network, Logistic Regression, kNN, SVM
7. Classification Based Machine Learning Algorithms - Naive Bayes, Discriminant Analysis, Decision Tree, Bagging and Boosting
8. Regression in Machine Learning - Linear and Non-Linear Regression
9. Regression in Machine Learning - SVM and Regression Tree
10. Clustering in Machine Learning - Hard Clustering
11. Clustering in Machine Learning - Soft Clustering
12. Dimensionality Reduction in Machine Learning
3. Fundamentals of Deep Learning
1. Definition of Deep Learning
2. Types of Deep Learning Techniques
4. Convolution Neural Network-based Architecture
5. Recurrent Neural Network-based Architecture
6. Convolution Recurrent Neural Network-based Architecture
7. Generative Adversarial Network-based Architecture
8. How to Design a Neural Network ?
9. List of Layers in Deep Neural Network
10. Training Parameters in Deep Learning