Dhairyya Agarwal is a product manager at Microsoft. He is based out of Mountain View, California where he is honing his product management skill set by solving problems in the email and collaboration security space. He received his master’s degree from Carnegie Mellon University in Software Management. He has delivered on many initiatives focused on improving retention, activation, and engagement. He has also worked across 0 to 1 products to enable businesses to enter a new markets. Shalini D is a quantum AI researcher at Fractal QuantumAI Lab researching quantum algorithms at the intersection of quantum chemistry and quantum machine learning. Previously, she worked at Infosys as a systems engineer, where she worked as a core customization API developer. She has completed her naster's in quantum technology from CSIC-Universidad Internacional Menendez Pelayo, Spain. Her research areas include semiconductor spin qubits, quantum machine learning, and quantum chemistry. She has taught quantum computing, from basic to advanced levels, at many universities, including Vellore Institute of Technology, India. She has also delivered several talks at various universities. Her Udemy course on the Qiskit Developer Exam is the highest-rated and bestseller globally. Srinjoy Ganguly is a quantum AI research scientist at Fractal QuantumAI Lab and a clinical Professor of Practice for Quantum Technology at Woxsen University. He is also an Associate Supervisor (adjunct) at the University of Southern Queensland in Australia, supervising PhD students in Quantum Machine Learning. He is an IBM Qiskit Advocate and an IBM Quantum Educator with over 5+ years of experience in quantum technologies. He is the author of the book Quantum Computing with Silq Programming, and has published several research papers in quantum chemistry, quantum machine learning, and quantum NLP. He possesses a triple master's in Quantum Technologies, Quantum Computing Technology and Artificial Intelligence (AI)  from CSIC-UIMP, Spain, Universidad Politecnica de Madrid and the University of Southampton, respectively. His research interests include superconducting quantum circuits, hybrid superconducting-semiconducting heterostructures (1D & 2D), topological quantum computing, spin qubits, quantum machine learning, quantum chemistry, quantum natural language processing and quantum AI.

Select Guide Rating

• Chapter 1: Introduction to Quantum Computing.- Chapter 2: Quantum Algorithms and Applications.- Chapter 3: Continue Learning About Quantum Computing.- Chapter 4: Assessing the Market and Competitive Landscape.- Chapter 5: Designing Quantum Products and Services.- Chapter 6: Developing a Quantum Roadmap.- Chapter 7:Integrating Quantum Computing into an Existing System.- Chapter 8:Releasing Quantum Computing-based Products.- Chapter 9: Challenges and Risk in Productizing Quantum Computing.

Dhairyya Agarwal is a product manager at Microsoft. He is based out of Mountain View, California where he is honing his product management skill set by solving problems in the email and collaboration security space. He received his master’s degree from Carnegie Mellon University in Software Management. He has delivered on many initiatives focused on improving retention, activation, and engagement. He has also worked across 0 to 1 products to enable businesses to enter a new markets. Shalini D is a quantum AI researcher at Fractal QuantumAI Lab researching quantum algorithms at the intersection of quantum chemistry and quantum machine learning. Previously, she worked at Infosys as a systems engineer, where she worked as a core customization API developer. She has completed her naster's in quantum technology from CSIC-Universidad Internacional Menendez Pelayo, Spain. Her research areas include semiconductor spin qubits, quantum machine learning, and quantum chemistry. She has taught quantum computing, from basic to advanced levels, at many universities, including Vellore Institute of Technology, India. She has also delivered several talks at various universities. Her Udemy course on the Qiskit Developer Exam is the highest-rated and bestseller globally. Srinjoy Ganguly is a quantum AI research scientist at Fractal QuantumAI Lab and a clinical Professor of Practice for Quantum Technology at Woxsen University. He is also an Associate Supervisor (adjunct) at the University of Southern Queensland in Australia, supervising PhD students in Quantum Machine Learning. He is an IBM Qiskit Advocate and an IBM Quantum Educator with over 5+ years of experience in quantum technologies. He is the author of the book Quantum Computing with Silq Programming, and has published several research papers in quantum chemistry, quantum machine learning, and quantum NLP. He possesses a triple master's in Quantum Technologies, Quantum Computing Technology and Artificial Intelligence (AI)  from CSIC-UIMP, Spain, Universidad Politecnica de Madrid and the University of Southampton, respectively. His research interests include superconducting quantum circuits, hybrid superconducting-semiconducting heterostructures (1D & 2D), topological quantum computing, spin qubits, quantum machine learning, quantum chemistry, quantum natural language processing and quantum AI.

Select Guide Rating

• Chapter 1: Introduction to Quantum Computing.- Chapter 2: Quantum Algorithms and Applications.- Chapter 3: Continue Learning About Quantum Computing.- Chapter 4: Assessing the Market and Competitive Landscape.- Chapter 5: Designing Quantum Products and Services.- Chapter 6: Developing a Quantum Roadmap.- Chapter 7:Integrating Quantum Computing into an Existing System.- Chapter 8:Releasing Quantum Computing-based Products.- Chapter 9: Challenges and Risk in Productizing Quantum Computing.

Dhairyya Agarwal is a product manager at Microsoft. He is based out of Mountain View, California where he is honing his product management skill set by solving problems in the email and collaboration security space. He received his master’s degree from Carnegie Mellon University in Software Management. He has delivered on many initiatives focused on improving retention, activation, and engagement. He has also worked across 0 to 1 products to enable businesses to enter a new markets. Shalini D is a quantum AI researcher at Fractal QuantumAI Lab researching quantum algorithms at the intersection of quantum chemistry and quantum machine learning. Previously, she worked at Infosys as a systems engineer, where she worked as a core customization API developer. She has completed her naster's in quantum technology from CSIC-Universidad Internacional Menendez Pelayo, Spain. Her research areas include semiconductor spin qubits, quantum machine learning, and quantum chemistry. She has taught quantum computing, from basic to advanced levels, at many universities, including Vellore Institute of Technology, India. She has also delivered several talks at various universities. Her Udemy course on the Qiskit Developer Exam is the highest-rated and bestseller globally. Srinjoy Ganguly is a quantum AI research scientist at Fractal QuantumAI Lab and a clinical Professor of Practice for Quantum Technology at Woxsen University. He is also an Associate Supervisor (adjunct) at the University of Southern Queensland in Australia, supervising PhD students in Quantum Machine Learning. He is an IBM Qiskit Advocate and an IBM Quantum Educator with over 5+ years of experience in quantum technologies. He is the author of the book Quantum Computing with Silq Programming, and has published several research papers in quantum chemistry, quantum machine learning, and quantum NLP. He possesses a triple master's in Quantum Technologies, Quantum Computing Technology and Artificial Intelligence (AI)  from CSIC-UIMP, Spain, Universidad Politecnica de Madrid and the University of Southampton, respectively. His research interests include superconducting quantum circuits, hybrid superconducting-semiconducting heterostructures (1D & 2D), topological quantum computing, spin qubits, quantum machine learning, quantum chemistry, quantum natural language processing and quantum AI.

Select Guide Rating

• Chapter 1: Introduction to Quantum Computing.- Chapter 2: Quantum Algorithms and Applications.- Chapter 3: Continue Learning About Quantum Computing.- Chapter 4: Assessing the Market and Competitive Landscape.- Chapter 5: Designing Quantum Products and Services.- Chapter 6: Developing a Quantum Roadmap.- Chapter 7:Integrating Quantum Computing into an Existing System.- Chapter 8:Releasing Quantum Computing-based Products.- Chapter 9: Challenges and Risk in Productizing Quantum Computing.