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Start Learning AI &Quantumat Rs.499Drive Innovation and StayAheadLearn AI & Quantum from IISc And QpiAI
You’ve taken a
Step in the rightdirection.
35,000+Data Engineer jobopenings in India with anaverage salary of 10.5LPA
₹48k CroreThe Indian AI market isvaluation as of August2020.
Source: Indeed
Source: Analytics India Magazine
Source: Dun & Bradstreet
Source: AI Multiple
40%of global organizationsare adding more jobsdue to AI adoption.
₹7.1k CroreThe global quantumcomputing market worthby 2025.
Course OverviewDiscover AI and Quantum from the fundamentals and
advance your way through Artificial Intelligence
algorithms, Machine Learning techniques and Quantum
programs. Gain strong foundational technical knowledge
and write, build, test, train and deploy AI/ML/Quantum
solutions. Throughout the course, you will be introduced
to real-world problems and applications to prepare you
for what the future holds.
Learning Experience
Self PacedLearningLearn on your schedule
Assignments & ProjectsGuided learning and implementation
IndustryPerspectiveTaught by industryleaders and professors
100%OnlineTheory and practical
Live InteractionsDoubt clearing sessions
Access India’sMostAdvancedQuantumSimulatorQpiAI Explorer is an offline learning tool thatoutstandingly combines the power of AIand Quantum within the same platform. Ithelps you learn, prepare, generate andpredict AI/ML models along with simulatingadvanced quantum circuits.
CollaborateWithEnterprises and SellYour SolutionsWith the know-how you gain through thecertification, you can build AI models,Quantum solutions and earn by directlyselling them to businesses on QpiAIMarketplace.
Secure a Certificate*from theWorld’s TopResearch Universityand QpiAIMaster AI and Quantum along with expertsfrom Indian Institute of Science, QpiAIleaders and secure a value-addedcertification for your resume to boost yourcareer credentials.
*Certification fee applicable.
Why Learn With Us?
Accelerate your career growth with
In(dustry)-DepthCurriculum
AI FoundationDip your toes in the field of AI
Chapter 1: Prerequisites forArtificial Intelligence(Contains 1 Module)
1.1 Linear Algebra
1.2 Probability Theory, Bayes Theoremand Statistics
1.3 Calculus and Optimization
Chapter 2: MachineLearning(Contains 3 Modules)
Supervised Machine Learning:
2.1 Introduction to Machine Learning,Supervised and Unsupervisedtechniques
2.2 Linear and Multiple LinearRegression, Performance Metrics,Regularization
2.3 Classification Models: KNN, LogisticRegression
2.4 Support Vector Machines;Classification Performance Metrics
2.5 Decision Trees, Bagging, Boostingand Ensemble Algorithms
Unsupervised Machine Learning:
2.6 Dimensionality Reduction: PCA
2.7 Clustering: K-Means Clustering
Chapter 3: Deep Learning(Contains 7 Modules)
3.1 Introduction to Deep Learning,Activation Functions, FeedforwardNetwork
3.2 Back Propagation, Loss Functions,Hyperparameter Tuning
3.3 Convolutional Neural Networks(CNN)
3.4 CNN Architectures for ImageClassification
3.5 Recurrent Neural Networks
3.6 Long Short-Term Memory Models
3.7 Autoencoders
Chapter 4: ReinforcementLearning(Contains 7 Modules)
4.1 Introduction to ReinforcementLearning and Multi Armed Bandits
4.2 Markov Decision Processes
4.3 Dynamic Programming (Value andPolicy Iteration)
4.4 Monte-Carlo Methods (On-policyand Off-Policy Algorithms)
Bonus: Practical Hands-onSession(Contains 6 Modules)
5.1 Machine Learning model generationwith scikit-learn
5.2 Deep Learning model generationwith PyTorch
Explorer Membership1 Month Included
& Access 1st Module
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All Chapters in AI Foundation+
Chapter 5: Special Topicsin Machine Learning(Contains 6 Modules)
5.1 Dimensionality Reduction: t-SNE,Kernel PCA, Spectral Clustering
5.2 Exploratory Data Analysis
5.3 Feature Engineering,Hyperparameter Tuning, ModelSelection
Chapter 6: AdvancedTopics in Deep Learning(Contains 6 Modules)
6.1 Object Detection
6.2 Semantic Segmentation
6.3 Generative Adversarial Networks
6.4 Variational Autoencoders
Chapter 7: AdvancedReinforcement Learning(Contains 7 Modules)
7.1 Q-learning, Temporal DifferenceMethods
7.2 Function Approximation, DQN
7.3 Policy Gradient Techniques andActor Critic Methods
Chapter 8: BayesianMethods in MachineLearning(Contains 5 Modules)
8.1 Bayesian Inference
8.2 Bayesian Optimization
8.3 Variational Methods
8.4 Gaussian Process Regression
Bonus: Practical Hands-onSession(Contains 6 Modules)
9.1 Machine Learning model generationwith scikit-learn
9.2 Deep Learning model generationwith PyTorch
9.3 Reinforcement Learning agenttraining in openAI Gym
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AI ExpertDive Deep into AI & ML
Explorer Membership1 Month Included
& Access 1st Module
Start withINR 499
All Chapters in AI Foundation+
Chapter 5: Special Topicsin Machine Learning(Contains 6 Modules)
5.1 Dimensionality Reduction: t-SNE,Kernel PCA, Spectral Clustering
5.2 Exploratory Data Analysis
5.3 Feature Engineering,Hyperparameter Tuning, ModelSelection
Chapter 6: AdvancedTopics in Deep Learning(Contains 6 Modules)
6.1 Object Detection
6.2 Semantic Segmentation
6.3 Generative Adversarial Networks
6.4 Variational Autoencoders
Chapter 7: AdvancedReinforcement Learning(Contains 7 Modules)
7.1 Q-learning, Temporal DifferenceMethods
7.2 Function Approximation, DQN
7.3 Policy Gradient Techniques andActor Critic Methods
Chapter 8: BayesianMethods in MachineLearning(Contains 5 Modules)
8.1 Bayesian Inference
8.2 Bayesian Optimization
8.3 Variational Methods
8.4 Gaussian Process Regression
Bonus: Practical Hands-onSession(Contains 6 Modules)
9.1 Machine Learning model generationwith scikit-learn
9.2 Deep Learning model generationwith PyTorch
9.3 Reinforcement Learning agenttraining in openAI Gym
1300 Hours worth of QpiAI-Pro access on QpiCloudwith GPU Instance
QpiAI™ Pro is the most collaborativeway to ideate ML & AI Models. Engage inthe next level of futuristic innovations inAI/ML.
10.1 Model discovery using Pro
10.2 model generation and Automl
10.3 Model deployment on edge devicesand cloud
10.4 End to End Project 1 with 48 hrs ofcloud usage (Student can chooseproject)
10.5 End to End Project 2 with 96 hrs ofcloud usage (Student can chooseproject)
10.6 End to End Project 3 with 198 hrs ofcloud usage (Student can chooseproject)
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AI ProBecome The AI Grandmaster
Explorer Membership1 Month Included
& Access 1st Module
Start withINR 499
QuantumFoundationDip your toes in the field of Quantum
Chapter 1: Prerequisites forQuantumComputing(Contains 1 Module)
1.1 Essential Linear Algebra
1.2 Basics of Quantum Mechanics
1.3 General Lecture on QuantumTechnology
1.4 Essential Computer Science
Chapter 2: QuantumStates and Qubits(Contains 8 Module)
2.1 Single-qubit states andsuperposition
2.2 Single-qubit gates andmeasurements
2.3 Two-qubit states, entanglement,and Bell’s inequality
2.4 Two-qubit gates and observable
2.5 Multi-Qubit states (GHZ and Wstates)
2.6 Universal gates and quantum circuitmodel
2.7 Quantum adiabatic computationand the Ising model
Chapter 3: QuantumAlgorithms(Contains 8 Modules)
3.1 Quantum Circuits
3.2 Deutsch-Jozsa Algorithm
3.3 Bernstein-Vazirani Algorithm
3.4 Quantum Fourier Transform
3.5 Quantum Factoring: Shor’sAlgorithm
3.6 Quantum Database Search: Grover’sAlgorithm
3.7 Circuit Simulations on QpiAI ExplorerSoftware
Chapter 4: QuantumProtocols(Contains 8 Modules)
4.1 Quantum Teleportation
4.2 Superdense Coding
4.3 Simulation of QpiAI ExplorerSoftware
4.4 Quantum Cryptography and KeyDistribution
4.5 Quantum Communication andNetworks
4.5 Guest Lecture - QKD,Communications
Chapter 5: QuantumHardware:Superconducting Qubits(Contains 10 Modules)
5.1 Introduction to physical qubits
5.2 Circuit Quantum Electrodynamics
5.3 Transmon and Coupled Qubits
5.4 Control and Readout
Chapter 6: QuantumProjects: Foundation(Contains 6 Modules)
6.1 Quantum Foundation Project 1
6.2 Quantum Foundation Project 2
6.3 Quantum Foundation Project 3
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Explorer Membership1 Month Included
& Access 1st Module
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Quantum ExpertDive deep into Quantum
All Chapters in Quantum Foundation+
Chapter 7: NISQ Devices(Contains 7 Modules)
7.1 Noise Models
7.2 Quantum Error Mitigation
7.3 Quantum Volume and PerformanceMetrics
7.4 Hybrid Quantum-ClassicalComputing
Chapter 8: QuantumAlgorithms forApplications(Contains 6 Modules)
8.1 Quantum Inspired Computing
8.2 Variational Quantum Algorithms
8.3 Variational Quantum Eigensolver
8.4 Quantum Approximate OptimizationAlgorithm
8.5 Quantum Machine Learning: QNNs
8.6 HHL Algorithm for Solving LinearSystems
Chapter 9: QuantumHardware:Semiconducting Qubits(Contains 10 Modules)
9.1 Introduction to physical qubits
9.2 Spin Physics and Quantum Dots
9.3 Control and Readout
9.4 Scalability
Chapter 10: QuantumProjects: Expert(Contains 6 Modules)
10.1 Quantum Expert Project 1
10.2 Quantum Expert Project 2
10.3 Quantum Expert Project 3
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Explorer Membership1 Month Included
& Access 1st Module
Start withINR 499
All Chapters in AI Expert+
Chapter 1: Prerequisites forQuantumComputing(Contains 1 Module)
1.1 Essential Linear Algebra
1.2 Basics of Quantum Mechanics
1.3 General Lecture on QuantumTechnology
1.4 Essential Computer Science
Chapter 2: QuantumStates and Qubits(Contains 8 Module)
2.1 Single-qubit states andsuperposition
2.2 Single-qubit gates andmeasurements
2.3 Two-qubit states, entanglement,and Bell’s inequality
2.4 Two-qubit gates and observable
2.5 Multi-Qubit states (GHZ and Wstates)
2.6 Universal gates and quantum circuitmodel
2.7 Quantum adiabatic computationand the Ising model
Chapter 3: QuantumAlgorithms(Contains 8 Module)
3.1 Quantum Circuits
3.2 Deutsch-Jozsa Algorithm
3.3 Bernstein-Vazirani Algorithm
3.4 Quantum Fourier Transform
3.5 Quantum Factoring: Shor’sAlgorithm
3.6 Quantum Database Search: Grover’sAlgorithm
3.7 Circuit Simulations on QpiAI ExplorerSoftware
Chapter 4: QuantumProtocols(Contains 8 Module)
4.1 Quantum Teleportation
4.2 Superdense Coding
4.3 Simulation of QpiAI ExplorerSoftware
4.4 Quantum Cryptography and KeyDistribution
4.5 Quantum Communication andNetworks
4.5 Guest Lecture - QKD,Communications
Chapter 5: NISQ Devices(Contains 7 Modules)
5.1 Noise Models
5.2 Quantum Error Mitigation
5.3 Quantum Volume and PerformanceMetrics
5.4 Hybrid Quantum-ClassicalComputing
Chapter 6: QuantumAlgorithms forApplications(Contains 6 Modules)
6.1 Quantum Inspired Computing
6.2 Variational Quantum Algorithms
6.3 Variational Quantum Eigensolver
6.4 Quantum Approximate OptimizationAlgorithm
Joint AI &Quantum Expert
Explorer Membership1 Month Included
& Access 1st Module
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6.5 Quantum Machine Learning: QNNs
6.6 HHL Algorithm for Solving Linear Systems
Chapter 7: QuantumHardware:Superconducting Qubits(Contains 10 Module)
7.1 Introduction to physical qubits
7.2 Circuit Quantum Electrodynamics
7.3 Transmon and Coupled Qubits
7.4 Control and Readout
Chapter 8: QuantumHardware:Semiconducting Qubits(Contains 10 Modules)
8.1 Introduction to physical qubits
8.2 Spin Physics and Quantum Dots
8.3 Control and Readout
8.4 Scalability
Chapter 6: QuantumProjects: Foundation(Contains 6 Modules)
6.1 Quantum Foundation Project 1
6.2 Quantum Foundation Project 2
6.3 Quantum Foundation Project 3
Chapter 10: QuantumProjects: Expert(Contains 6 Modules)
10.1 Quantum Expert Project 1
10.2 Quantum Expert Project 2
10.3 Quantum Expert Project 3
CourseWrap-up and Future Directions
Found a topic you’reinterested in?
Learn In-Demand SkillsFrom Global Leaders
Prof. ShalabhBhatnagarProfessor,Dept. of ComputerScience and Automation.
Indian Institute of Science,Bangalore.
Dr. NagendraNagarajaCEO& Founder,QpiAI India.
PhD, Coventry University UK.
Prof. Ujjwal SenProfessor,QuantumInformation & ComputationGroup.
Harish-Chandra ResearchInstitute, Allahabad.
Dr. AmlanMukherjeeDirector QuantumHardwareResearch,QpiAI India.
PhD, TIFR India.
Dr. Arun SehrawatQuantumResearch Scientist,QpiAI India.
PhD, National University ofSingapore.
Pinakin PadaliaDirector QuantumCircuits,QpiAI India.
MS, TU Delft Netherlands.
LakshyaPriyadarshiSoftware and AlgorithmsResearcher,QpiAI India.
B.Tech, Institute of Engineering& Technology.
Aswanth KrishnanDirector QuantumResearch,QpiAI India.
MSc, NIT Karnataka.
That’s not all.
And more guest lecturersfrom India and Abroad.
Sachin KumarDirector of AI Research,QpiAIIndia.
B.Tech, NIT Trichy.
Make Your NextMove Towards YourCareer Goals
Sign up on QpiAI ExplorerLogin on the QpiAI Explorer panel using your email ID &password / sign up with a new account.
Start learning from expertsStart with Rs.499, get QpiAI Explorer Membership for 1month and unlock access to 1st Module. Pay per moduleand upgrade to more as you learn.
Become a verified AI andQuantum solutions sellerExcel in assignments and exams, get certified from IIScand QpiAI, earn by becoming a verified seller on QpiAIMarketplace.
Learn at your own pace andimprove your knowledgeLearn at your own pace by renewing the QpiAI ExplorerMembership to keep course access. Membershipincludes exclusive benefits like the Explorer application,live discussions, forum and more.
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AI FoundationGet complete course for 3 months atRs.19,990
QuantumFoundationGet complete course for 3 months atRs.19,990
AI ExpertGet complete course for 6 months atRs.29,990
Quantum ExpertGet complete course for 6 months atRs.29,990
AI ProGet complete course for 6 months atRs.1,00,000
Joint AI &Quantum ExpertGet complete course for 6 months atRs.49,990
Course FeeStart Learning Any Course at just Rs.499Get access to 1stmodule and 1 Month QpiAI Explorer Membership. Pay per module and learn at yourown pace. Retain course & explorer access with Rs.499/month after 1st month
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