Duration

2.5 months

Format

Live Online Instructor-led

Certificate From

IIT Roorkee

Lab Duration

180 Days

Sign up for Free Webinar on Introduction to Machine Learning on May 31

About the Course

Have you ever wondered how self-driving cars are running on roads or how Netflix recommends the movies which you may like or how Amazon recommends you products or how Google search gives you such an accurate results or how speech recognition in your smartphone works or how the world champion was beaten at the game of Go?

Machine learning is behind these innovations. In the recent times, it has been proven that machine learning and deep learning approach to solving a problem gives far better accuracy than other approaches. This has led to a Tsunami in the area of Machine Learning.

Most of the domains that were considered specializations are now being merged into Machine Learning. This has happened because of the following:

  • Better research and algorithms
  • Better computing resources
  • Distributed computing infrastructures
  • Availablity of Big Data

Every domain of computing such as data analysis, software engineering, and artificial intelligence is going to be impacted by Machine Learning. Therefore, every engineer, researcher, manager or scientist would be expected to know Machine Learning.

So naturally, you are excited about Machine learning and would love to dive into it. This specialization is designed for those who want to gain hands-on experience in solving real-life problems using machine learning and deep learning. After finishing this specialization, you will find creative ways to apply your learnings to your work.

Program Highlights

  • Certificate of Completion by IIT Roorkee

  • 45+ Hours of Learning

  • Instructor led Training

  • Projects, Case Studies & Assignments

  • Exclusive Lab Access

Certificate

What is the certificate like?

  • Why IIT Roorkee?

    IIT Roorkee has been ranked the best among IITs, as per the QS World Best Universities Ranking 2019. Established in 1847, it's the oldest technical institutions in Asia.

    IIT Roorkee fosters a very strong entrepreneurial culture. Some of their alumni are highly successful as entrepreneurs in the new age digital economy.

  • Why Cloudxlab?

    CloudxLab (CxL) has been a pioneer in the edtech space for the past few years. Founded in 2015 by Sandeep Giri, an alumnus of IIT Roorkee, CxL has successfully transformed 1,000's of students' careers by offering world-class certification courses in big data, machine learning and artificial intelligence.

    Some of the unique features of CxL are an exclusive gamified learning environment through the lab (read as CloudxLab), highest rated faculty, excellent student support and more.

Instructors

Instructor Sandeep Giri

Sandeep Giri

Founder at CloudxLab

Past: Amazon, InMobi, D.E.Shaw

Instructor Abhinav Singh

Abhinav Singh

Co-Founder at CloudxLab

Past: Byjus

Instructor Durga Toshniwal

Durga Toshniwal

Professor

IIT Roorkee

Instructor Gaurav Dixit

Gaurav Dixit

Assistant Professor

IIT Roorkee

Instructor Praveen Pavithran

Praveen Pavithran

Co-Founder at Yatis

Past: YourCabs, Cypress Semiconductor

Curriculum

45+
Hours of Training
180
Days of Lab Access
10+
Projects
1. Introduction to Linux (Self-Paced)
In this topic, we will learn the basics of Linux. Sound Linux skills help in data cleaning, deploying models in production and finding potential bottlenecks
2. Python for Machine Learning (Self-Paced)
In this topic, we will learn the foundations of Python, NumPy, Pandas, Matplotlib and Linear Algebra. These foundations will help in building Machine Learning and Deep Learning models.
3. Statistics Foundations (Self-Paced)
In this topic, we will learn foundations of statistics including probability, measures of central tendencies (mean, median and mode), measures of spread(range, quartiles and interquartile range, variance, and standard deviation) and normal distribution.
4. Introduction to Machine Learning and Deep Learning
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.
5. Data Preprocessing, Regression - Build end-to-end Machine Learning Project
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
6. Classification
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.
7. Machine Learning Algorithms
In this topic, we will learn various Machine Learning algorithms and concepts like Unsupervised Learning, Ensemble Learning, and Dimensionality Reduction
8. Introduction to Artifical Neural Networks with Keras
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
9. Training Deep Neural Networks
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.
10. Custom Models and Training with TensorFlow
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.
11. Loading and Preprocessing Data with TensorFlow
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.
12. Deep Computer Vision using Convolutional Neural Network
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
13. Processing Sequences Using RNNs and CNNs
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
14. Natural Language Processing Concepts and RNNs
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.
15. Representation Learning & Generative Learning Using autoencoders and GANs
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.
16. Reinforcement Learning
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.

Projects

Testimonials

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Eligibility Criteria

  • Having or pursuing Bachelor's degree in Science / Engineering / Technology / Mathematics
  • Experience with any programming language

Application Process

  • 1. Submit the application form with basic details (including motivation to join the course) followed by a quiz
  • 2. The admission team will review the application and respond with the application status in 48 hours
  • 3. Confirmation of seat is subject to the payment

Scholarship Details

  • IIT Alumni - 5% discount for max 15 max users
    • First come first serve basis
    • Document (Photocopy of ID Card/ Degree/ Alumni Card) required for verification
  • Based on Online Scholarship Test
    1. Scholarship test for the 2nd Batch will be conducted on 21 June 2020 (Timing 4:00-6:00 PM IST). There will be MCQs from basic Programming and Maths. Test link will be circulated before one day of the test date. Top 10 Users will get 10% discount, then 5% discount for next 5 Users.
  • If you receive the Scholarship, you will need to make full payment and then the amount will be refunded.

699*

  • Timing 8:00-11:00PM (IST) Sat-Sun
  • 45+ Hours of Live Online Instructor-led Learning
  • 100+ hours of self-paced content
  • 180 Days of Online Lab Access
  • 24*7 Support
  • Certificate from IIT Roorkee
Batch 1 is Sold Out
  • Batch 1 starts from May 31st 2020
  • Apply Now for Batch 2
  • Batch 2 starts from June 28th 2020
  • We are in the news

    Frequently Asked Questions

    Course/Certificate Details

    What is the format of the course?

    The content will be a mix of interactive self-paced lectures and live instructor-led training from industry leaders as well as renowned faculty from IIT Roorkee. Linux and Python will be provided as self-paced module before the live classes start. Additionally, the program comprises 24*7 support dedicated to solving your academic queries and reinforcing learning. The discussion forum on the CloudxLab website will also facilitate peer-to-peer interactions.

    What is the criteria for getting the course completion certificate?

    Criteria to get the course completion certificate is following-

    1. 1. Minimum 60% attendance in live instructor-led classes.
    2. 2. All mandatory topics in LMS have to be at least 70% complete.
    3. 3. Complete minimum 6 projects out of above listed 11 projects.

    What is the criteria for getting the course and project completion certificate?

    The major project will be outside of the above 11 projects and will be assigned by faculty. Criteria of course completion certificate are met and the assigned major project is successfully completed by Aug 17, 2020.

    Expectations/Scope

    What can I expect out of this course?

    You will learn all the concepts of machine learning and deep learning. Expect to carry out several industry-relevant projects simulated as per the actual workplace. At the end of the course you will be a skilled Artificial Intelligence and Deep Learning professional as per leading industry standards.

    How the 'Advanced Certification Course on Deep Learning ' is beneficial for students?

    If we look at the current trend in the market, it is very clear that every company is moving towards artificial intelligence. Every company is looking for problem solvers. Deep Learning is one of the most sought after skills in the market these days for solving any problem. With the current global situation, there is going to be a demand in highly skilled professionals in Deep Learning across all the verticals making this the perfect time to utilize the perks of online learning.

    How a 'Deep Learning course' is different from other Machine learning and Artificial intelligence courses available in India?

    AI stands for Artificial Intelligence. Machine Learning is a branch of computer science in which we study how to achieve AI or teach machines to predict given data.
    Deep Learning is part of Machine Learning in which we achieve AI using artificial neural networks. Machine Learning is in practice for many decades but it has been mostly by statistical methods. Recently, there have been tremendous advancements in the field of Deep Learning. For example, the turing award of 2018 was awarded for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. The primary focus of this course is the Deep Learning component.
    This course is an adequate mix of Applied and Theoretical Computing because it is being delivered by a group of Professors from IITs and Industry practitioners.
    This course has a Cloud based Lab provided by CloudxLab and a unique auto assessment engine which checks the works of the user instantaneously.

    What is the scope of Deep Learning in market?

    The performance of Deep Learning algorithms is way better than classic machine learning algorithms. There are many problems related to AI which seemed impossible to solve with standard machine learning are now very much feasible with Deep Learning.
    This is the reason why companies are moving to Deep Learning based solutions. Deep Learning is used today in recognizing people (face recognition), detecting a threat, building a robot or making an autonomous car. Deep Learning is being used in conjunction with existing techniques to derive efficient solutions.
    Earlier, there used to be people specialized in various fields Audio processing, video processing, Image Processing etc. Today, these all branches are merging into a Deep Learning or AI.

    Eligibility Criteria and Process

    My current job does not require any learning of AI and Machine Learning. Does it make sense for me to opt for this program?

    Yes! ML/AI has become a necessity for all industries. Hence, there is a critical demand for AI Engineers in market. Due to lack of quality data professionals, it provides the highest paying job opportunities across all the industries.​

    What is the selection process for this program?

    World-renowned faculty of IIT-Roorkee and many industry leaders have committed a lot of time in designing, conceptualising and creating this program to make sure that the learners can have the best possible learning experience in AI and deep learning. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for the same. The applicants will have to submit an application form followed by an aptitude test. The admission committee will review your application and respond with your application status in 48 hours after submitting the application form.

    Is there any minimum educational qualification or pre-requisite to take this program?

    To be eligible for the program, both criteria need to be fulfilled:

    1. 1. Qualification: Having or pursuing Bachelor's degree in Science / Engineering / Technology / Mathematics.
    2. 2. Basic Coding Knowledge: The applicant should be comfortable with at least one of the Programing Languages.

    Financials/ Scholarship

    Is there any refund policy for this program?

    We will provide 100% refund if request is raised before 11:59PM (IST) 12 June 2020 for Batch 1 and 5 July 2020 for Batch 2. After that no refund request will be entertained hence, there will be no full/partial refund.

    I cannot pay the course fee at a time. Is there any EMI option?

    We do not have EMI options as of now. If you are making payment using Instamojo, you can opt for EMI option on their portal. Please note that Instamojo payment gateway is only available for Indian users. Please check this link for more details here

    Is there any scholarship for the course?

    Yes, there are will be two scholarships as follows. You can avail only one scholarship from both.

    1. 1. IIT Alumni: 5% discount for max 15 users (first come first serve) To avail this scholarship you need to provide a picture of your college ID card/degree/alumni-card for the verification over the mail.
    2. 2. Online Scholarship Test: Scholarship test for Batch 2 will be conducted on 21 June 2020 (Timing 4:00-6:00PM IST). There will be MCQs from basic Programming and Maths. Test link will be circulated before one day of test date. Top 10 Users will get 10% discount, then 5% discount for next 5 Users.
    3. 3. If you receive the Scholarship, you will need to make full payment and then the amount will be refunded.

    Is there any bulk discount available?

    We will provide 5% discount on each if more than 10 people want to enroll together in the course.

    Is there any discount for referral for this program?

    We'd appreciate if you tell your friends and colleagues about Artificial Intelligence and Deep Learning course by IIT Roorkee. Referrer as well as Referred, both get 3% cashback on the course price (INR 49,999/USD 699). Here is how it works: -> Share the referred details with us -> Get enrolled in the AI-DL course -> Cashback would be initiated on June 12, 2020.

    Time and Schedule

    What is the application process for the program and what are the timelines?

    Applications have already started for this course. You can start the application process by submitting the application form and eligibility quiz. Then our admission committee will take a call on approval and revert back. After making the payment you will get access for the self paced content, then live classes of Batch 1 will start from 31st May 2020 and Batch 2 will start from 28th June 2020.

    What is the time commitment expected for the program?

    At least 12-15 hours (6 hours live session + 6 to 9 hours for assessments and projects) per week of time commitment is expected for the program.

    Tech/Career Support

    What if I miss any classes in between?

    Recording of every session will be available just after the class, even if you miss the class you can go through the recording and ask your doubts either on our discussion forum or in the next class.

    What if I can't understand certain topics in the class?

    You can directy ask and discuss your doubts in the class with the instructor. You can also put your query on discussion forum. We have a dedicated support team to resolve learner's issue.

    Do i need to install or buy any software for this course?

    No, You do not need to install any software for this course. We will provide all the required infrastructure with a cloud-based virtual lab for practice.

    Expected career options after pursuing this course?

    Someone who has successfully completed this course is expected to be able to solve problems more efficiently using some of the latest technologies in the industry.
    Learners who have completed this course will be perfect fit for job roles like Machine Learning Engineer, AI Engineer, Deep Learning Engineer, Data Scientist etc.

    What type of career support should I expect from this program?

    1. 1. Preparatory Support: Mentoring on how to make the best resume for a AI/ML Engineer, highlighting technical and domain expertise. Artificial Intelligence and Deep Learning interview mentoring by industry experts.
    2. 2. Job Assistance: Profiles of students will be circulated in CloudxLab’s network of companies. For many learners, it would be very hard to switch their job in AI industry immediately. For them, it's more about how to inculcate data-driven leadership in the current job and plan a transition into Artificial Intelligence or Deep Learning in the medium-to-long run.