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Artificial Intelligence Combo Pack

Upskill yourself with the most in-demand career choice of AI with our Artificial Intelligence Combo Pack.

Whether you’re just learning to code or already have experience, you’ll find this course helpful you develop your skills and advance your projects.

In this training you will learn various aspects of AI like Deep Learning with Pytorch, Machine Learning, Artificial Neural Networks, Expert systems, Object Detection and Vernacular Language Signboard Translation as a Capstone Project.

You will get 12 Deep Learning module certificates and 3 final certificate.This program will prepare you to solve real world problems using cutting edge technologies.

Key Features
  • Course taught by IIT Madras Professors who are subject matter experts in the field.
  • 100+ hours of self paced videos with Lifetime Access.
  • 15 Modules certifications.
  • Globally Recognized Certificate from GUVI after successful completion
  • Dedicated Forum Support from the Instructors
  • 100% Online Learning
  • Access to community of DL Students and Enthusiasts
  • Frequent Kaggle contests
  • 7 days Refund Policy
  • Time commitment of 4 hours a week.
  • Laptop / desktop with internet access.
What you'll get in this pack
  • Python
  • Machine Learning
  • Deep Learning
Who Should Enroll in this course
  • IT Professionals
  • IT Consultants
  • IT Graduates & Freshers
  • Any Graduate with Programming Knowledge
Fee structure
Eligibility Students enrolled in schools/colleges without any prior work experience and faculty members of colleges and universities. Requisites Applicants must provide a valid details indicating their present enrolment in any recognised educational institution. Fee Structure 16800 3699 (You Save: 78% )
Eligibility Working professionals from companies and any other applicant with work-experience looking to upskill. Requisites Nil. Just apply directly. Fee Structure 16800 8399 (You Save: 50% )
About instructors
Arun Prakash is the Founder & Chief Technology Officer of GUVI. He is a technologist with more than 17 years of experience. He has worked with bigwigs like Paypal, Symantec & Honeywell in the past.
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing high-quality content for technical skill development. Loonycorn is working on developing an engine (patent filed) to automate animations for presentations and educational content.
Mitesh M. Khapra is an Assistant Professor in the Department of Computer Science and Engineering at IIT Madras. He researches in the areas of Deep Learning, Multimodal Multilingual Processing, Dialog systems and Question Answering. He holds masters and Ph.D degrees from IIT Bombay. He has worked for over 4.5 years at IBM Research and published over 25 papers. He was a recipient of IBM PhD Fellowship and the Microsoft Rising Star Award. He is also a recipient of the Google Faculty Research Award, 2018.
Pratyush is an Assistant Professor at the Department of Computer Science and Engineering at IIT Madras since April 2018. He received his Bachelors and Masters of Technology in Electrical Engineering from IIT Bombay in 2009. He then completed his PhD in Computer Engineering from ETH Zurich in 2014. He then spent over 2.5 years at IBM Research, Bangalore and a few months consulting for machine learning and startups. His current research focus is on hardware-software co-design of deep learning systems. He has authored over 35 research papers and has applied for over 20 patents.

DL#101 - Getting Started

37 Lesson

10 hrs

DL#102 - Primitive Neurons

38 Lesson

10 hrs

DL#103 - Sigmoid Neuron

57 Lesson

10 hrs

DL#105 - Training Feedforward Neural Networks

41 Lesson

10 hrs

DL#106 - Optimization Algorithms

70 Lesson

10 hrs

DL#108 - Convolutional Neural Networks

24 Lesson

10 hrs

DL#109 - Deep Convolutional Neural Networks

61 Lesson

10 hrs

DL#110 - Sequence Models

61 Lesson

13 hrs

DL#111 - Encoder Decoder Models

25 Lesson

5 hrs

DL#113 - Capstone Project

1 Lesson

1 hrs

View all 13 Modules

View less

For futher queries, Write a mail to [email protected]
Sample certificate
Our learners

"This course is the best as it focuses both on the theory and hands on.This course introduced me to Kaggle competitions and I got addicted to it.I feel more confident that I can contribute to real world projects involving deep learning after taking this course."

"Learned a lot from this course. Before starting this course, I have no knowledge of deep learning but after learning this course I am pretty confident."

"This course can turn you into a deep learning enthusiast if you have the urge to learn something new (even if you don't know anything about deep learning at all)."

About Deep Learning
Deep learning refers to a set of techniques by which we can achieve varying degrees of artificial intelligence by mimicking the working of a human brain. Deep learning is a subset of Machine Learning techniques that aim to achieve Artificial Intelligence. The distinguishing feature of Deep Learning is its use of various Artificial Neural Networks, that imitate the human brain. Just as in the brain, Artificial Neural Networks or ANNs also consist of neurons and synapses between them. Deep Learning vs Machine Learning: In traditional Machine Learning, the data must be broken down into individual features. These hand-crafted features are fed into the model and we get a prediction as an output. However, hand-crafting features is a time-consuming process that involves a lot of statistical knowledge and expertise in data science. With the advent of Deep Learning and multi-layered Artificial Neural Networks, feature selection can now be handled by the model itself. By feeding it numerical representation of raw data (Images, Video, Audio etc), the multi-layered architecture allows for the model to determine the highest-contributing features and uses them to make successful predictions, without any human crafted features. This drastically shortened project timelines and human intervention in the preliminary stages. A small caveat is that DL models required larger volumes of data to train than traditional ML models. Advantages of Studying Artificial Intelligence: From SIRI to self-driving cars, artificial intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons. Let us discuss some of the advantages studying Artificial Intelligence..
  • Automates the processes: Artificial Intelligence allows robots to develop repetitive, routine and process optimization tasks automatically and without human intervention.
  • Enhance creative tasks: AI frees people from routine and repetitive tasks and allows them to spend more time on creative functions.
  • Helps in Daily Applications: Daily applications such as Apple’s Siri, Window’s Cortana, Google’s OK Google are frequently used in our daily routine whether it is for searching a location, taking a selfie, making a phone call, replying to a mail and many more.
  • Quick Learning: With around 5-8 hours of study per week and around 6 months of time, learners can progress rapidly from novice to intermediate/adept levels with this AI Combo Pack.
Artificial Intelligence Career Opportunities: Projects @ IT/ITeS Companies: For those looking to transition into AI projects at IT companies, familiarity of programming, application and mathematics behind deep learning will be suitable. DL products @ startups: For those looking to join startups focused on AI products, a working level of proficiency in programming, mathematics and application of AI techniques would be required. Research @ universities, research labs: For those looking to enter the research field, expert understanding of Artificial Intelligence, its underlying concepts and its practical application are required.
Why study through GUVI?
Guvi is an IIT-M , IIM-A incubated company located at IITM Research Park, Chennai. We help students master any programming skills so that they can learn and effectively practice the acquired knowledge and skills necessary to thrive in their career. Our feature includes practicing exercises, instructional videos, and a personalized learning dashboard that empowers learners to study at their own pace.
Partner with us
Universities and Colleges If you are an educational institution and would like to adopt our courses for your curriculum, we are very happy to support you. We can bulk enrol your students and provide certification for them to receive appropriate credit at your institution.
Foundations and NGOs If you are a foundation or an NGO and find synergy with our goal of affordable AI education, you can offer support for curriculum design and awards for top- performing students.
Corporates and Startups If you would like to train several of your employees on AI, please write to us to receive customized reports on how they perform. You can also partner with us on the DL garage by defining problem statements and awarding student grants.
Frequently Asked Questions
How is this different from other courses?
The focus of the courses is primarily on combining theoretical knowledge with hands-on experience. Further, the emphasis is to go from limited pre-requisites to solving a challenging problems. Finally, we hope to build a community around PadhAI by continuing to engage with you after the course through the DL garage, subsequent courses, and also through our startup One Fourth Labs which will build solutions on Deep Learning.
Will I get a certificate on completing a course?
Yes, upon successful completion, you will get a certificate from GUVI. This certificate will be accessible to you.
What are the pre-requisites?
We do not expect you to be familiar with AI or related topics. Mathematical understanding equivalent to 12th standard syllabus would be sufficient. However, the course requires a time commitment of 4 hours per week.
How can I ask my doubts?
We will have discussion forums where you can discuss the topics covered and ask doubts. Your peers or our Teaching assistants will answer the questions. Additionally, there will periodical video calls once a fortnight where instructors will answer questions.
An IIT-M & IIM-A Incubated Company