Post Graduate Certificate in Advanced Machine Learning & AI
Offered By: Indian Institute of Technology Roorkee via Coursera
Course Description
Overview
Artificial Intelligence (AI) and related technologies are revolutionising everyday life around the world. Given the increasing adoption of AI and Deep Learning (DL) innovations across industries—such as Alexa, Siri, humanoids, and chatbots—there is a growing demand for AI talent across industries. Those aspiring to build a career in AI and DL can get a head-start with this advanced certificate.
In this six-month comprehensive program, you will enhance your expertise of deep learning techniques and its applications in AI.
In this six-month comprehensive program, you will enhance your expertise of deep learning techniques and its applications in AI.
Syllabus
Course 1: Introduction to Tensorflow and Keras
- In this course, you will learn and develop the necessary knowledge and skills for the most prevalent machine learning libraries for the deep learning subdomain: Tensorflow and Keras.
Course 2: Machine Learning Projects Using Tensorflow and Keras
- In this course, Tensorflow and Keras would be used to implement End-to-end machine learning projects.
Course 3: Introduction to Artificial Neural Networks
- In this course, you will learn Artificial Neural Networks (ANN) concepts and algorithms. This course will cover the background of ANNs, evolution of ANN architectures, and modern developments.
Course 4: Deep Neural Networks
- Get introduced to the concept of a neuron and how multiple neurons can be used to construct an artificial neural network. Deep learning is a class of machine learning algorithms that progressively extract features for better understanding of the problem. You will learn about various deep learning models built using artificial neural networks.
Course 5: Convolutional Neural Networks and Computer Vision
- Artificial Intelligence (AI) has come a long way and has been seamlessly bridging the gap between the potential of humans and machine vision. The advancements in Computer Vision with Deep Learning have been a considerable success, particularly with the Convolutional Neural Network (CNN) algorithm. You will learn about CNN and various CNN models to solve Computer Vision problems.
Course 6: Recurrent Neural Networks and Sequence Modeling
- Processing the naturally spoken language is one of the complex tasks faced by researchers. In this module, you will learn about Natural Language Processing and how Deep Learning models can be used to build speech recognition applications.
Course 7: Application of AI Capstone
- Learn about cutting edge applications of Artificial Intelligence with the Image Captioning Capstone project. This will be an end-to-end project to apply the concepts taught in the program. Many forms of media frequently lack alternative text for images. This lack of image captions hampers the accessibility of their content. Hiring people to write captions for those pictures is often prohibitively expensive. The use of an automated system to write the captions would be a viable alternative. The objective of the project is to develop such a system which can generate descriptive captions for a given image.
- In this course, you will learn and develop the necessary knowledge and skills for the most prevalent machine learning libraries for the deep learning subdomain: Tensorflow and Keras.
Course 2: Machine Learning Projects Using Tensorflow and Keras
- In this course, Tensorflow and Keras would be used to implement End-to-end machine learning projects.
Course 3: Introduction to Artificial Neural Networks
- In this course, you will learn Artificial Neural Networks (ANN) concepts and algorithms. This course will cover the background of ANNs, evolution of ANN architectures, and modern developments.
Course 4: Deep Neural Networks
- Get introduced to the concept of a neuron and how multiple neurons can be used to construct an artificial neural network. Deep learning is a class of machine learning algorithms that progressively extract features for better understanding of the problem. You will learn about various deep learning models built using artificial neural networks.
Course 5: Convolutional Neural Networks and Computer Vision
- Artificial Intelligence (AI) has come a long way and has been seamlessly bridging the gap between the potential of humans and machine vision. The advancements in Computer Vision with Deep Learning have been a considerable success, particularly with the Convolutional Neural Network (CNN) algorithm. You will learn about CNN and various CNN models to solve Computer Vision problems.
Course 6: Recurrent Neural Networks and Sequence Modeling
- Processing the naturally spoken language is one of the complex tasks faced by researchers. In this module, you will learn about Natural Language Processing and how Deep Learning models can be used to build speech recognition applications.
Course 7: Application of AI Capstone
- Learn about cutting edge applications of Artificial Intelligence with the Image Captioning Capstone project. This will be an end-to-end project to apply the concepts taught in the program. Many forms of media frequently lack alternative text for images. This lack of image captions hampers the accessibility of their content. Hiring people to write captions for those pictures is often prohibitively expensive. The use of an automated system to write the captions would be a viable alternative. The objective of the project is to develop such a system which can generate descriptive captions for a given image.
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