Certificate Course on Artificial Intelligence and Deep Learning
Explore more the aspects of deep learning and its effects in field of machine learning with the ‘Certificate Course on Artificial Intelligence and Deep learning
Online
39,999 INR Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Certificate Course on Artificial Intelligence and Deep Learning program is organized and offered by the Indian Institute of Technology in Roorkee on the Cloudxlab online education and innovation platform.
The courses study is about the principles and techniques involved in deep learning which is the basis for many recent innovations. In this course, the participants will gain a thorough knowledge of deep learning and machine learning with the best curriculum. The course educators include the faculties from IIT Roorkee Raksha Sharma(CSE dept) and Gaurav Dixit(DoMS dept) and the founder Sandeep Giri and Cofounders of Cloudxlab Abhinav Singh and Praveen Pavithran.
The programming languages and tools that are used during the course study are TensorFlow, Keras, Learn, Numpy, Pandas, and Python.
The Highlights
- Online mode
- Doubt resolution
- 180 hours of Cloudlab access
- Job assistance
- IIT Roorkee certification
- Expert guidance
Programme Offerings
- Course Modules
- Twelve Projects
- Cloudlab Access
- Technical Support
- Gamified Learning Platform
- Automatic Evaluation of Assessment
- Professional Mentors
- Programming Tools
- Scholarships
- Career Guidance
- Webinars
- Testimonials
- IIT Roorkee Certificate.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Roorkee |
Certificate Course on Artificial Intelligence and Deep Learning fee structure
| Fees components | Amount in INR |
Total Course Fee | Rs 39,999 |
Monthly installment | Rs 6,666 |
Eligibility Criteria
Certificate qualifying details:
The candidates who have taken the ‘Certificate Course on Artificial Intelligence and Deep Learning’ are required to complete 75% of the course materials with any three mandatory real-world projects within 180 days of registration to qualify for the certificate issued by the Indian Institute of Technology Roorkee.
What you will learn
The ‘Certificate Course on Artificial Intelligence and Deep Learning’ syllabus is designed for the students to gain an understanding of the techniques involved in deep learning and the other aspects of machine learning that drive the technologies. The increased scope of research and algorithms in the industry is explored through this program. The presence of big data and computing resources have enabled the study and research in deep learning. This course provides the candidates with the skills for deep learning, programming, and the knowledge about the different software tools and programming languages with an understanding of the domain of artificial intelligence. At the end of the Certificate Course on Artificial Intelligence and Deep Learning classes, the students will be able to decipher real-world solutions with the help of deep learning.
Who it is for
The ‘Certificate Course on Artificial Intelligence and Deep Learning’ online training is for software engineers, data analysts, and those who work with artificial intelligence to improve their knowledge on deep learning. The machine learning knowledge gained during this course benefits the engineers, managers, researchers, and data scientists to excel in their careers as it enhances their problem-solving process.
Admission Details
The course admission to the ‘Certificate Course on Artificial Intelligence and Deep Learning’ training is done through the official website of Cloudxlab.
Step 1: Go to the course page on the Cloudxlab website using the link below,
https://cloudxlab.com/course/84/certificate-course-artificial-intelligence-deep-learning-iit-roorkee
Step 2: Click on the ‘Apply now’ link on the course page.
Step 3: Fill in the application form and send in the statement of purpose.
Step 4: The response to the application will be sent in 48 hours
Step 5: Complete the payment and confirm the admission.
Application Details
The candidates who wish to apply for the ‘Certificate Course on Artificial Intelligence and Deep Learning’ will have to register for the course by filling in the application form found on the registration page.
The Syllabus
- Linux for Data Science/ Machine Learning
- Getting Started with Git
- Python Foundations
- Machine Learning Prerequisites(Including Numpy, Pandas, and Linear Algebra)
- Getting Started with SQL
- Statistics Foundations
- In this topic, we will cover concepts like different types of Machine Learning algorithms (Supervised, Unsupervised, Reinforcement) and challenges in Machine Learning. We will see examples of solving the problems using the traditional approach and why Machine Learning algorithms give far better accuracy than the traditional approach. This topic will give you a brief introduction to both Machine Learning and Deep Learning world.
- We will start the course by learning concepts in Machine Learning. In this topic, we will build a machine learning model to predict housing pricing in California. By the end of this project, you will understand how to build machine learning pipelines to build a model. We will also cover concepts like data cleaning, preparing data for machine learning algorithms, exploring many different models, short-list the best one and fine-tuning the selected model
- In this topic, we will train a model on the MNIST dataset to recognize handwritten digits. We will also learn various performance measures in classification like Confusion Matrix, Precision and Recall, and ROC Curve.
- In this topic, we will learn various Machine Learning algorithms and concepts like Unsupervised Learning, Ensemble Learning, and Dimensionality Reduction
- We will start the Deep Learning course with Artificial Neural Networks. We will learn about biological neurons, multilayer perceptrons, and back-propagation. We will implement a multilayer perceptron using Keras and visualize the runs and graphs using Tensorboard
- In this topic, we will learn various challenges deep neural networks face while training like vanishing and exploding gradients. We will learn various techniques to solve these problems like reusing pre-trained layers, using faster optimizers and avoiding overfitting by regularization.
- In this topic, we will dive deeper into TensorFlow and its lower level Python API. These lower-level Python APIs are useful when we need extra control like writing custom loss function, layers and many more.
- Deep Learning systems are usually trained on very large datasets that may not fit in the RAM. In this topic, we will learn TensorFlow's Data API which helps in ingesting dataset and preprocessing it efficiently.
- In this topic, we will learn how Convolutional Neural Networks - CNNs achieve superhuman performance on complex visual tasks. Today CNNs power image search services, self-driving cars, automatic video classification systems and more. We will learn CNNs basic building blocks and how to implement them using TensorFlow and Keras
- Predicting the future is something we do all the time like predicting stock prices. In this topic, we will learn how Recurrent Neural Networks - RNN predict the future, the problem they face like limited short-term memory and solutions to these problems - LSTM (Long Short-Term Memory) and GRU cells
- Using Natural Language Processing we build systems that can read and write natural language. In this topic, we will learn different NLP techniques and generate Shakespearean text using a Character RNN.
- Autoencoders are artificial neural networks capable of learning dense representations of input data without any supervision. For example, we could train an autoencoder on pictures of faces and it can then generate new faces. In this topic, we will learn different types of autoencoders and generative models.
- Reinforcement Learning is one of the most exciting fields of Machine Learning. Using Reinforcement Learning AlphaGo(system) defeated the world champion at the game of Go. Reinforcement Learning is an area of Machine Learning aimed at creating agents capable of taking actions in an environment in a way that maximizes rewards over time. In this topic, we will learn various concepts in Reinforcement Learning and experiment with OpenAI Gym.
Instructors
IIT Roorkee Frequently Asked Questions (FAQ's)
This online training course includes a total of 12 projects that provide a hands-on experience with the concepts of deep learning.
There is no mandatory prerequisite for this course.
The candidates are provided access to the online lab and BootML by Cloudxlab in the ‘Certificate Course on Artificial Intelligence and Deep Learning’ hence there is no need for any preinstallation.
Yes, after the self-learning course, the eligible candidates are issued the certificate from IIT Roorkee.