8 Quantum Computing courses

If you are new to Quantum computing, then this course will help you understand the fundamentals and practicalities of this field. This course will provide you with step-by-step guidance in learning the implementation and important methodologies associated with Quantum computing in a beginner-friendly environment.

This course is intended for beginner-level individuals who are fascinated about quantum computing and want to learn more about it. It uses Jupyter notebook and IBM Qiskit tool to execute your learning into the actual computation.

“Quantum Computing for Finance” is a 2-course online program designed for learners to realize the true potential of quantum technologies and its use-cases in Finance. The first course “Introduction to Quantitative and Computational Finance” will develop fundamental concepts required for an understanding of quantum algorithms and more advanced topics in computational finance. This course will teach you the basics of derivative products, the Black-Scholes-Merton model for pricing vanilla derivatives, and how to compute the price of exotic options with a computer. The second course “Quantum Algorithms for Computational Finance” is an advanced course that will develop an understanding of quantum algorithms for their implementation on quantum computers and their applications in finance. This course covers several aspects of quantum programming for people already familiar with the basics of quantum programming and quantitative finance. Buy the program at a reduced price.

About the course “Quantum Computing for Finance” is an emerging multidisciplinary field of quantum physics, finance, mathematics, and computer science, in which quantum computations are applied to solve complex problems. “Quantum Algorithms for Computational Finance” is an advanced course in the emerging field of quantum computing for finance. This technical course will develop an understanding in quantum algorithms for its implementation on quantum computers. Through this course, you will learn the basics of various quantum algorithms including: Grover’s and Rudolf’s algorithm, Quantum amplitude Estimation (QAE) algorithm envisioned as a quadratic speed-up over Classical Monte-Carlo simulations, Combinatorial optimization algorithms namely Quantum Approximate Optimization Algorithm (QAOA), and Variational Quantum Eigensolver (VQE), and Quantum-inspired optimization algorithms – Simulated Coherent Ising Machine (Sim-CIM), and Simulated Bifurcation Algorithm (SBA). This course is meant for all those learners who want to explore the long-term employability of quantum computing in finance, assuming that you are familiar with the concepts of quantitative and computational finance. In addition, the course contains several Python based programming exercises for learners to practice the algorithms explained throughout the course. This course is the second part of the specialised educational series: “Quantum Computing for Finance”. What Skills you will learn Ability to perform quantum arithmetic operations and simulations. An understanding of the Quantum Amplitude Estimation algorithm and its variants. The computational and modelling techniques for option pricing and portfolio optimization on a quantum computer. The skills for a career in quantum finance including Quantum Algorithmic Research, Quantitative Asset Management and Trading, financial engineering, and risk management, using quantum computing technology. Course Prerequisites All potential learners must have prior knowledge or familiarity with basic quantum algorithms/basic quantum programming. Before enrolling this course, we recommend all learners to complete the first course “Introduction to Quantitative and Computational Finance” of the series “Quantum Computing for Finance”, if they have no previous experience with the concepts of quantitative and computational finance. Duration The estimated duration to complete this course is approximately 6 weeks (~4hrs/week). Course assessment To complete the course and earn the certification, you must pass all the quizzes at the end of each lesson by scoring 80% or more on each of them. Instructors QuantFiQuantFi is a French start-up research firm formed in 2019 with the objective of using the science of quantum computing to provide solutions to the financial services industry. With its staff of PhD's and PhD students, QuantFi engages in fundamental and applied research in in the field of quantum finance, collaborating with industrial partners and universities in seeking breakthroughs in such areas as portfolio optimisation, asset pricing, and trend detection.

A second quantum revolution with far reaching applications is unfolding. This non-technical course will teach you how to navigate the rise of quantum technologies and its applications across industries. Whether you want to know what’s behind the buzzwords or whether you want to perhaps use quantum technologies yourself either in a personal context or in a corporation or other organisation, this course will teach you how. There is no prerequisite for taking this course.

About the course “Quantum Computing for Finance” is an emerging multidisciplinary field of quantum physics, finance, mathematics, and computer science, in which quantum computations are applied to solve complex problems. “Introduction to Quantitative and Computational Finance” provides a basis to step into the world of Quantum Computing for Finance. This introductory course will develop fundamental concepts required for an understanding of quantum algorithms and more advanced topics in computational finance. Through this course, you will learn the basics of derivative products, the Black-Scholes-Merton model for pricing vanilla derivatives, and how to compute the price of exotic options with a computer. This course is designed for all those who wish to develop their skills and start a career in quantitative finance. This course is the first part of the specialised training program: “Quantum Computing for Finance”. What Skills you will learn The fundamentals of derivative products, their types – forwards and options, and their pricing. An understanding of the Black-Scholes-Merton model, hedging and volatility modelling. The computational and modelling techniques for pricing options such as Monte-Carlo simulations and the Finite Difference method. A strong foundation in quantitative and computational skills for modelling and solving complex financial problems using Python programming language. The skills for a career in the finance industry, including quantitative asset management and trading, financial engineering, risk management, and applied research. Course Prerequisites All potential learners should have prior knowledge of the following content areas, either through completion of academic studies or relative professional preparation: Basic calculus (partial derivatives) Probability theory (with an exposure to measure theory if possible) Basic linear algebra (matrix operations) Numerical Python (NumPy essentially) The course contains several Python based programming exercises. We recommend that you install Python on your local system to practice and implement the programs explained throughout the course. For instructions and tutorials for beginners, please click on the following link: Python installation instructions and tutorials for beginners Duration The estimated duration to complete this course is approximately 4 weeks (~3hrs/week). Course assessment To complete the course and earn certification, you must pass all the quizzes at the end of each lesson by scoring 80% or more. Instructors QuantFiQuantFi is a French start-up research firm formed in 2019 with the objective of using the science of quantum computing to provide solutions to the financial services industry. With its staff of PhD's and PhD students, QuantFi engages in fundamental and applied research in in the field of quantum finance, collaborating with industrial partners and universities in seeking breakthroughs in such areas as portfolio optimisation, asset pricing, and trend detection.

Duration 1 Days 6 CPD hours This course is intended for This course does not have any technical knowledge prerequisites for the learners, besides being proficient in using a computer and the Internet. IT and/or AI knowledge is a benefit but not a hard requirement. Given the rapid development of AI and the broad range of its applications in everyday life, it is crucial for anyone to attend this course to update their digital skills in an ever-changing world. It is expected that all learners have registered for a free account of OpenAI ChatGPT at https://chat.openai.com. Overview Discover how AI relates to other 4th industrial revolution technologies Learn about AI, ML, and associated cognitive services Overview of AI development frameworks, tools and services Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail The core aim of this ?AI for beginners? course is to introduce its audience to Artificial Intelligence (AI) and Machine Learning (ML) technologies and allow them to understand the practical applications of AI in their everyday personal and professional life. Moreover, the course aims to provide a handful of demos and hands-on exercises to allow the learners to familiarize themselves with usage scenarios of OpenAI ChatGPT and other Generative AI (GenAI) models. The content of this course has been created primarily by using the OpenAI ChatGPT model. AI theoretical concepts. Introduction to AI, ML, and associated cognitive services (Computer vision, Natural language processing, Speech analysis, Decision making). How AI relates to other 4th industrial revolution technologies (cloud computing, edge computing, internet of things, blockchain, metaverse, robotics, quantum computing). AI model classification by utilizing mind maps and the distinctive role of Gen AI models. Introduction to the OpenAI ChatGPT model and alternative generative AI models. Familiarization with the basics of the ChatGPT interface (https://chat.openai.com). Talking about Responsible AI: Security, privacy, compliance, copyright, legal challenges, and ethical implications. AI practical applications Overview of AI development frameworks, tools and services. AI aggregators review. Hand-picked AI tool demos: a.Workplace productivity and the case of Microsoft 365 Copilot. b.The content creation industry. Create text, code, images, audio and video with Gen AI. c.Redefining the education sector with AI-powered learning. Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail: a.Prompting and plugin demos. b.Code interpreter demos. Closing words. Discussion with an AI model on the future of AI. Additional course details: Nexus Humans AI for beginners training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AI for beginners course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for The intended audience for this comprehensive course on Information Assurance and STIGs includes professionals with roles such as: IT professionals - System administrators, network engineers, and security analysts who are responsible for maintaining and securing IT infrastructure and web applications. Developers - Software engineers and web developers who design, implement, and maintain web applications, and need to integrate security best practices throughout the development process. Project teams - Cross-functional teams that collaborate on application development projects, including members from development, testing, and deployment teams. Technical leads - Senior software engineers or architects who oversee technical aspects of projects and ensure the implementation of secure design and coding practices. Project managers - Professionals responsible for planning, executing, and closing projects, ensuring that security requirements are met throughout the project lifecycle. Overview Working in an interactive learning environment, guided by our application security expert, you'll explore: The concepts and terminology behind defensive coding Threat Modeling as a tool in identifying software vulnerabilities based on realistic threats against meaningful assets The entire spectrum of threats and attacks that take place against software applications in today's world The role that static code reviews and dynamic application testing to uncover vulnerabilities in applications The vulnerabilities of programming languages as well as how to harden installations The basics of Cryptography and Encryption and where they fit in the overall security picture The requirements and best practices for program management as specified in the STIGS The processes and measures associated with the Secure Software Development (SSD) The basics of security testing and planning Understand the concepts and terminology behind defensive coding Understand Threat Modeling as a tool in identifying software vulnerabilities based on realistic threats against meaningful assets Learn the entire spectrum of threats and attacks that take place against software applications in today's world Discuss the role that static code reviews and dynamic application testing to uncover vulnerabilities in applications Understand the vulnerabilities of programming language as well as how to harden installations Understand the basics of Cryptography and Encryption and where they fit in the overall security picture Understand the fundamentals of XML Digital Signature and XML Encryption as well as how they are used within the web services arena Understand the requirements and best practices for program management as specified in the STIGS Understand the processes and measures associated with the Secure Software Development (SSD) Understand the basics of security testing and planning The Information Assurance (STIG) Overview is a comprehensive two-day course that delves into the realm of Information Assurance, empowering you to enhance your cybersecurity skills, understand the essentials of STIGs, and discover cutting-edge web application security practices. This immersive experience is tailored for IT professionals, developers, project teams, technical leads, project managers, testing/QA personnel, and other key stakeholders who seek to expand their knowledge and expertise in the evolving cybersecurity landscape. The course focuses on the intricacies of best practices for design, implementation, and deployment, inspired by the diverse and powerful STIGs, ultimately helping participants become more proficient in application security.The first half of the course covers the foundations of DISA's Security Technical Implementation Guides (STIGs) and learn the ethical approach to bug hunting, while exploring the language of cybersecurity and dissecting real-life case studies. Our expert instrtors will guide you through the importance of respecting privacy, working with bug bounty programs, and avoiding common mistakes in the field.The next half delves into the core principles of information security and application protection, as you learn how to identify and mitigate authentication failures, SQL injections, and cryptographic vulnerabilities. You?ll gain experience with STIG walkthroughs and discover the crucial steps for securing web applications.Throughout the course, you'll also explore the fundamentals of application security and development, including checklists, common practices, and secure development lifecycle (SDL) processes. You?ll learn from recent incidents and acquire actionable strategies to strengthen your project teams and IT organizations. You'll also have the opportunity to explore asset analysis and design review methodologies to ensure your organization is prepared to face future cybersecurity challenges. DISA's Security Technical Implementation Guides (STIGs) The motivations behind STIGs Requirements that the various software development roles must meet Implementing STIG requirements and guidelines Why Hunt Bugs? The Language of CyberSecurity The Changing Cybersecurity Landscape AppSec Dissection of SolarWinds The Human Perimeter Interpreting the 2021 Verizon Data Breach Investigation Report First Axiom in Web Application Security Analysis First Axiom in Addressing ALL Security Concerns Lab: Case Study in Failure Safe and Appropriate Bug Hunting/Hacking Working Ethically Respecting Privacy Bug/Defect Notification Bug Bounty Programs Bug Hunting Mistakes to Avoid Principles of Information Security Secuity Is a Lifecycle Issue Minimize Attack Surface Area Layers of Defense: Tenacious D Compartmentalize Consider All Application States Do NOT Trust the Untrusted Identification and Authentication Failures Applicable STIGs Quality and Protection of Authentication Data Proper hashing of passwords Handling Passwords on Server Side Session Management HttpOnly and Security Headers Lab: STIG Walk-Throughs Injection Applicable STIGs Injection Flaws SQL Injection Attacks Evolve Drill Down on Stored Procedures Other Forms of Server-Side Injection Minimizing Injection Flaws Client-side Injection: XSS Persistent, Reflective, and DOM-Based XSS Best Practices for Untrusted Data Lab: STIG Walk-Throughs Applications: What Next? Common Vulnerabilities and Exposures CWE/SANS Top 25 Most Dangerous SW Errors Strength Training: Project Teams/Developers Strength Training: IT Organizations Cryptographic Failures Applicable STIGs Identifying Protection Needs Evolving Privacy Considerations Options for Protecting Data Transport/Message Level Security Weak Cryptographic Processing Keys and Key Management Threats of Quantum Computing Steal Now, Crack Later Threat Lab: STIG Walk-Throughs Application Security and Development Checklists Checklist Overview, Conventions, and Best Practices Leveraging Common AppSec Practices and Control Actionable Application Security Additional Tools for the Toolbox Strength Training: Project Teams/Developers Strength Training: IT Organizations Lab: Recent Incidents SDL Overview Attack Phases: Offensive Actions and Defensive Controls Secure Software Development Processes Shifting Left Actionable Items Moving Forward Lab: Design Study Review Asset Analysis Asset Analysis Process Types of Application-Related Assets Adding Risk Escalators Discovery and Recon Design Review Asset Inventory and Design Assets, Dataflows, and Trust Boundaries Risk Escalators in Designs Risk Mitigation Options