Learn Quantum & AI for Free.*
Get Certified from IISc & QpiAI.

QpiAI™ Quantum & AI Certification is an easy way to learn and immerse yourself into the world of Quantum Computing and Artificial Intelligence. Everything you need to learn Quantum and AI in one learning package!

*Pay only for certification.

Joint learning program by

Certification issued by IISc Bangalore
AI and quantum computing certification courses by experts

Courses from Experts

Courses are taught by Prof. Shalabh Bhatnagar(IISc), Prof. Ujwal Sen(HRI), QpiAI team and experts from around the world! The course content will be updated constantly. Download the complete information brochure here.

1 year free access on  AI and quantum computing certification courses

Upto 1 year free license for QpiAI Explorer*

QpiAI Explorer is the fastest and easiest way to learn and apply Quantum and AI Concepts. Learn more about QpiAI Explorer.

* – On purchase of certification course.

Certification from IISc and QpiAI

Certification from IISc and QpiAI

Get ahead of your peers with a recognized certification from IISc and QpiAI.

Learn

Artificial Intelligence

Artificial Intelligence
Machine Learning
Deep Learning
Learn Concepts on Artificial Intelligence

Artificial Intelligence

Learn Concepts on traditional Machine Learning

Machine Learning

Learn Concepts on Deep Learning

Deep Learning

Quantum Computing

Essential Mathematics
Quantum Computation
Quantum Information
Quantum Communication
Quantum Programming
Quantum Applications
Learn Essentials of Mathematics in the certification

Essential Mathematics

Learn basics of Quantum Computing in the certification

Quantum Computation

Learn basics of Quantum Information in the certification

Quantum Information

Learn basics of Quantum Communication in the certification

Quantum Communication

Learn basics of Quantum Programming in the certification

Quantum Programming

Learn scope of Quantum Applications in the certification

Quantum Applications

Available Certifications (4)

Entrance exam starts from: 30 July, 2021

Learn for free
Pay only for certification.

AI Certification – Beginner (Level 1)
 

For the ones who want to start learning learning Artificial Intelligence

Course Fee
Free Course

Certification Fee – INR 20,000
Scholarships Available#

Concepts Covered
 

Artificial Intelligence
Machine Learning
Deep Learning

Course type

Learn on demand

Duration

Self-paced

6 Months free access
Having Questions? Read the FAQ.

Joint Certification in AI and Quantum Computing

For the ones who want to dive deep into AI and Quantum

Course Fee
Free Course

Certification Fee – INR 50,000
Scholarships Available#

Concepts Covered in AI Certification (Level 2) +

Essential Mathematics
Quantum Computation
Quantum Information
Quantum Communication
Quantum Programming
Quantum Applications

Course type

Learn on demand

Duration

Self-paced

1 Year free access
Having Questions? Read the FAQ.

AI Certification – Advanced (Level 2)

For the ones who want a comprehensive course on Artificial Intelligence

Course Fee
Free Course

Certification Fee – INR 30,000
Scholarships Available#

Concepts Covered in Level 1 +

Practical and Advanced Machine Learning
Advanced Topics in Deep Learning

Course type

Learn on demand

Duration

Self-paced

1 Year free access
Having Questions? Read the FAQ.

AI Certification – Pro

For the ones who want a comprehensive course on Artificial Intelligence & the whole QpiAI software suite

Course Fee
Free Course

Certification Fee – INR 1,00,000
Scholarships Available#

Having Questions? Read the FAQ.

Concepts Covered in
AI Level 1 +

Practical and Advanced Machine Learning
Advanced Topics in Deep Learning

Course type

Learn on demand

Duration

Self-paced

Software Included

1 Year free access
Free Cloud Compute Credits Worth
50,000 INR*

*T&C Apply. Credits will be provided in QpiAI Pro.

AI Certification – Beginner (Level 1)
 

For the ones who want to start learning learning Artificial Intelligence

Course Fee
Free Course

Certification Fee – INR 20,000
Scholarships Available#

Concepts Covered
 

Artificial Intelligence
Machine Learning
Deep Learning

Course type

Learn on demand

Duration

Self-paced

6 Months free access
Having Questions? Read the FAQ.

Joint Certification in AI and Quantum Computing

For the ones who want to dive deep into AI and Quantum

Course Fee
Free Course

Certification Fee – INR 50,000
Scholarships Available#

Concepts Covered in AI Certification (Level 2) +

Essential Mathematics
Quantum Computation
Quantum Information
Quantum Communication
Quantum Programming
Quantum Applications

Course type

Learn on demand

Duration

Self-paced

1 Year free access
Having Questions? Read the FAQ.

AI Certification – Advanced (Level 2)

For the ones who want a comprehensive course on Artificial Intelligence

Course Fee
Free Course

Certification Fee – INR 30,000
Scholarships Available#

Concepts Covered in Level 1 +

Practical and Advanced Machine Learning
Advanced Topics in Deep Learning

Course type

Learn on demand

Duration

Self-paced

1 Year free access
Having Questions? Read the FAQ.

AI Certification – Pro

For the ones who want a comprehensive course on Artificial Intelligence & the whole QpiAI software suite

Course Fee
Free Course

Certification Fee – INR 1,00,000
Scholarships Available#

Concepts Covered in AI Level 1 +

Practical and Advanced Machine Learning
Advanced Topics in Deep Learning

Course type

Learn on demand

Duration

Self-paced

Software Included

1 Year free access
Free Cloud Compute Credits Worth
50,000 INR*

*T&C Apply. Credits will be provided in QpiAI Pro.

Having Questions? Read the FAQ.

#Scholarships will be available for top scorers in the entrance test. T&C Apply.
*EMI Options Available.

> See Course Curriculum

AI Certification – Beginner (Level 1)

Chapter 1: Prerequisites for Artificial Intelligence
1.1 Linear Algebra
1.2 Probability Theory
1.3 Bayes Theorem and Statistics
1.4 Calculus and Optimization
Chapter 2: Supervised Machine Learning
2.1 Regression Models
2.2 Linear and Multiple Linear Regression
2.3 Regression Performance Metrics
2.4 Classification Models
2.5 KNN, Logistic Regression
2.6 Support Vector Machines
2.7 Confusion Matrix, ROC Curves
2.8 Decision Tree, Bagging, Boosting and Ensembling
Chapter 3: Unsupervised Machine Learning
3.1 Dimensionality Reduction: PCA
3.2 Clustering: K-Means Clustering
Chapter 4: Deep Learning
4.1 Activation Functions, Feedforward Network
4.2 Back Propagation, Loss Functions, Hyperparameters
4.3 Convolutional Neural Networks
4.4 CNN Architectures for Image Classification
4.5 Recurrent Neural Networks
4.6 Long Short-Term Memory Models
4.7 Autoencoders
Chapter 5: Reinforcement Learning
5.1 Finite Markov Decision Processes
5.2 Value and Policy Iteration (Dynamic Programming)
5.3 Monte-Carlo Methods
5.4 On-policy and Off-Policy Algorithms

Joint Certification Program in Artificial Intelligence & Quantum Computing

Curriculum Covered in AI Certification (Level 2) and the following

Chapter 1: Prerequisites for Quantum Computing
1.1 Essential Linear Algebra
1.2 Essential Computer Science
1.3 Basics of Quantum Mechanics
Chapter 2: Quantum States and Qubits
2.1 Single-qubit states and superposition
2.2 Single-qubit gates and measurements
2.3 Two-qubit states, entanglement, and Bell’s inequality
2.4 Two-qubit gates and observable
2.5 Multi-Qubit states (GHZ and W states)
2.6 Universal gates and quantum circuit model
2.7 Quantum adiabatic computation and the Ising model for NP-hard problems
Chapter 3: Quantum Algorithms
3.1 Quantum Circuits
3.2 Deutsch-Jozsa Algorithm
3.3 Bernstein-Vazirani Algorithm
3.4 Quantum Fourier Transform
3.5 Quantum Factoring: Shor’s Algorithm
3.6 Quantum Database Search: Grover’s Algorithm
3.7 Circuit Simulations on QpiAI Explorer Software
Chapter 4: Quantum Protocols
4.1 Quantum Teleportation
4.2 Superdense Coding
4.3 Simulation of QpiAI Explorer Software
4.4 Quantum Cryptography and Key Distribution
4.5 Quantum Communication and Networks
Chapter 5: NISQ Devices
5.1 Noise Models
5.2 Quantum Error Mitigation
5.3 Quantum Volume and Performance Metrics
5.4 Hybrid Quantum-Classical Computing
Chapter 6: Quantum Algorithms for Applications
6.1 Quantum Inspired Computing
6.2 Variational Quantum Algorithms
6.3 Variational Quantum Eigensolver
6.4 Quantum Approximate Optimization Algorithm
6.5 Quantum Machine Learning: QNNs
6.6 HHL Algorithm for Solving Linear Systems
Chapter 7: Quantum Hardware: Superconducting Qubits
7.1 Introduction to physical qubits
7.2 Circuit Quantum Electrodynamics
7.3 Transmon and Coupled Qubits
7.4 Control and Readout
Chapter 8: Quantum Hardware: Semiconducting Qubits
8.1 Introduction to physical qubits
8.2 Spin Physics and Quantum Dots
8.3 Control and Readout
8.4 Scalability

AI Certification – Advanced (Level 2)

Chapter 1: Prerequisites for Artificial Intelligence
1.1 Linear Algebra
1.2 Probability Theory
1.3 Bayes Theorem and Statistics
1.4 Calculus and Optimization
Chapter 2: Supervised Machine Learning
2.1 Regression Models
2.2 Linear and Multiple Linear Regression
2.3 Regression Performance Metrics
2.4 Classification Models
2.5 KNN, Logistic Regression
2.6 Support Vector Machines
2.7 Confusion Matrix, ROC Curves
2.8 Decision Tree, Bagging, Boosting and Ensembling
Chapter 3: Unsupervised Machine Learning
3.1 Dimensionality Reduction: PCA
3.2 Clustering: K-Means Clustering
3.3 t-SNE
3.4 Kernel PCA
3.5 Spectral Clustering
Chapter 4: Deep Learning
4.1 Activation Functions, Feedforward Network
4.2 Back Propagation, Loss Functions, Hyperparameters
4.3 Convolutional Neural Networks
4.4 CNN Architectures for Image Classification
4.5 Recurrent Neural Networks
4.6 Long Short-Term Memory Models
4.7 Autoencoders
Chapter 5: Practical Machine Learning
5.1 Exploratory Data Analysis
5.2 Feature Engineering
5.3 Hyperparameter Tuning
5.4 Model Selection
5.5 End-to-end Machine Learning
Chapter 6: Bayesian Methods in Machine Learning
6.1 Bayesian Inference
6.2 Bayesian Optimization
6.3 Variational Methods
6.4 Gaussian Process Regression
Chapter 7: Advanced Topics in Deep Learning
7.1 Object Detection
7.2 Semantic Segmentation
7.3 Generative Adversarial Networks
7.4 Variational Autoencoders
Chapter 8: Reinforcement Learning and Deep Reinforcement Learning
8.1 Finite Markov Decision Processes
8.2 Value and Policy Iteration (Dynamic Programming)
8.3 Monte-Carlo Methods
8.4 On-policy and Off-Policy Algorithms
8.5 Deep Reinforcement Learning
8.6 Value-based methods and Q-learning
8.7 Function Approximation, DQN
8.8 Policy Gradient Methods, Actor Critic Methods

Course Structure

Certification course Study material for Quantum Computing and AI

Available for free
Study Material

We have curated an extensive in-depth curriculum for teaching Quantum Computing and Artificial Intelligence. We cover the basics of quantum mechanics, then expand on quantum circuits, algorithms, protocols, and their applications to various science and technology problems. In AI, we cover the basics of mathematics, and then cover traditional machine learning. We stress on supervised and unsupervised learning methods, and deep neural networks.

Certification course Assignments on Quantum Computing and AI

paid feature
Assignments, Projects & Forum

Students will be supplemented with exercises and assignments based on the study material. They will be guided to read and implement research papers and build projects based on state-of-the-art developments in Quantum Technologies and Artificial Intelligence

Project based learning on Quantum Computing and Artificial Intelligence

paid feature
QpiAI Explorer

Upto 1 Year License

QpiAI Explorer Software will enable the students to build quantum circuits and experiment with the simulation of quantum algorithms and protocols. Our tool provides detailed explanatory visualizations and even capability to simulate hybrid circuits. The software will also enable the students to build machine learning models and experiment on various classes of problems and datasets. It will teach the students to prepare data, run algorithms, train models, and build ML systems.

How does the course work?

1

Register and start learning for free

Anybody can register and learn from the course videos for free.

2

Take entrance test for certification

Interested users can apply to join the paid certification program by attending the entrance exam.
Students performing well will be allowed to take up the certification. Students performing extremely well will be given a scholarship.

3

Enroll in certification and get complete access

After enrollment, students will be granted access to QpiAI Explorer, forum and doubt clearning sessions

4

Excel and become a verified seller

Students who perform well in certification assignments and exam will get a verified certificate from IISc. and QpiAI.
Students who excel will get a chance to become a verified seller on QpiAI Marketplace.

How will you learn?

Theory Sessions
Practical Sessions
Assignments
Learn Online or with QpiAI™ Explorer Software

Certain features are only available on QpiAI™ Explorer.

Theory Session in certification course

Theory Sessions

Practical Session in certification course

Practical Sessions

Assignments in certification course

Assignments, Projects and Tests

QpiAI Explorer tool

Learn Online or with QpiAI™ Explorer Software

Certain features are only available on QpiAI™ Explorer.

Certification from IISc and QpiAI India on AI and Quantum Learning

Certificate shown is for representational purposes only. Actual certificate may vary.

Get Certified

Improve your resume with a certification from IISc and QpiAI India. What’s more? Students who perform excellently* get free 1-year license to QpiAI Pro and free 1-year license to the upcoming QpiAI AI/ML Model Marketplace as both buyer and seller.

*Students who secure above 90% in Level 2 AI Certification or Joint Certification on Quantum and AI are eligible for QpiAI Marketplace. For QpiAI Pro 1-year free license, cloud computation costs shall be borne by the student/user.

Frequently Asked Questions

1. How can I enroll in the certificate courses?
  • Once you know which course you want to take part in, click on “Sign up”
  • Register yourself by entering your basic details
  • Complete the sign up process by entering the verification code sent to your email
  • Click on the “Access Course” button next the course you want to register for
  • Take the entrance test on or after 30th Jul 2021
  • After passing the test, the “Enrol Now” will get activated on your screen (after an unsuccessful attempt, you can retake the test only after 3 months)
  • Chose the payment method of your convenience and make your payment for the certification (EMI options available with select banks)
  • Congratulations, you’re in! 
2. Is there an entrance test for the certification?

Yes, an entrance test is conducted before the enrolment and a score of 40% or above will be accepted into the course. If you score above 90%, you will also be eligible for upto 60% scholorship.

3. What are prerequisites for two sets of courses (Quantum, AI) in general?
We do not assume any prerequisites in any of the topics. We will start the course from absolute basics and build the grounds for all concepts required in AI and Quantum. However, basic understanding of matrices, vectors, complex numbers and functions will be helpful.
4. What will be the course structure for the 3 courses?
Here is a video explaining the course structure for the 3 courses:

You can also download the complete course information brochure here:

Download

5. What is the eligibility criteria for a certification program?

The course is open to school students, undergraduate students and postgraduate students in science, technology, and engineering, and to working professionals in any domain of the industry. The only criteria to take part in the course is a score of 40% or above in the entrance test. 

6. What is the mode delivery for the courses? Is it entirely online or requires physical presence?
The mode of the course is completely online in the form of pre-recorded lectures. The lectures will be streamed through the QpiAI Explorer tool.
7. What is the minimum system requirements for running QpiAI Explorer software?

Software will require the following setup to be installed and used:

OS: The software is currently available for

  1. Windows 10
  2. Linux; Recommended Ubuntu 20
  3. Mac OS: Recommended Catalina and Above

CPU: Intel or AMD processor with 64-bit support; Recommended: 2.8 GHz or faster processor

RAM: 4GB RAM; Recommended: 6 GB+

Disk Storage: 4 GB of free disk space

Monitor Resolution: 1280×800; Recommended: 1920×1080

Internet: Internet connection is required for software activation.

8. Can I watch a preview video for the course lecture?

Sure, here is one of the course lectures:

Course Introduction Video:

9. How would the hands-on component (projects/assignments) be completed/submitted?
The assignments will be in the form of coding notebooks. The evaluations will be automated.
10. How much weekly workload is expected? (in hours)
The weekly workload for
AI-Level 1 Course is 4.5 hours.
AI-Level 2 Course is 4.5 hours.
Joint AI and Quantum Course is 9 hours.
11. How will I get support for query resolution / project guidance during the course?
The QpiAI team will be live on the discussion forum and will support the resolution of queries as soon as they are posted.
12. Would there be guest lectures from the industry?
The course will have a set of guest lectures from esteemed professors and research practitioners. QpiAI itself being an industry organization will drive the course in an application-centric manner. We have curated the course in such a way that the balance between theory and applications is maintained. This will also reflect in the course assignments.
13. How long will the course material be accessible ?
  1. The AI Level-1 certification is a 3-months program.
  2. The AI Level-2 certification is a 6-months program.
  3. The Joint AI-Quantum Computing Certification is a 6-months program.
  4. Students for Level-1 AI Certification will have access to course materials for 6 months.
  5. Students for Level-2 AI and Joint AI+Quantum Certification will have 1 year access.
14. Would it help for an experienced professional like me to switch domains or do a career transition?
The course will cover applications of quantum computing to various domains like optimization, machine learning, finance, logistics, pharmaceuticals, space technology, and others. This would enable the professionals to develop quantum computational and AI solutions for diverse applications within and across their industries, and lead new research and development projects.

Highly motivated candidates might as well transition to the world of quantum computing technologies and take up roles in taking the industry forward.

15. Could top candidates get an opportunity to work at QpiAI?
QpiAI is committed to building a quantum ecosystem in India, and our certification program is the first step towards it. After successful completion of the course, excellent candidates (consolidating 90% + aggregate score) will

  1. Have an opportunity to be considered for AI as well as Quantum computing jobs at QpiAI
  2. Have 1-year QpiAI Pro License and 1 year free membership to QpiAI Marketplace AI and Quantum Solutions Marketplace
  3. The cloud computation cost for QpiAI Pro will be borne by the candidate
16. Still have questions?

You can also write to us at certification@qpiai.tech and our team will get back as soon as possible.

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