410 Courses

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

This award introduces the critical concepts associated with AI and explores its relationship with the systems and processes that make up the digital ecosystem. It explores how AI can empower organisations to utilise Big Data through the use of Business Analysis and Machine Learning, and encourages candidates to consider a future vision of the world that is powered by AI.

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Thinking about learning about Knowledge-Based Systems? The BCS Foundation Certificate in Artificial Intelligence teaches learners to recognise Knowledge-Based Systems (such as chat bots), gain an understanding of how they work, and consider how they can add value to an organisation. This award will also enable candidates to understand the concept of Uncertainty and Fuzzy Logic, and how Knowledge-Based Systems can be used to help organisations to make decisions and act where there is higher level of uncertainty. You will learn an understanding of Knowledge-Based Systems and their role within AI, the use of rules within a Knowledge-Based System, an understanding of the principles of case-based reasoning, an understanding of uncertainty and the use of fuzzy logic and an understanding of the role of the inference engine.

Who can apply for this MBA – Artificial Intelligence program? Anyone with an undergraduate degree with a minimum of 50% marks Minimum of one year of professional experience Professionals looking to grow their career with a Master degree in Management Professionals wishing to make a transition to mid-level and higher positions

Who is this course for? Sketchup Artificial Intelligence Training Course. Mastering SketchUp Artificial Intelligence (AI) is essential for designers, offering automation, efficiency, and innovative solutions. It saves time, enhances visualizations, fosters collaboration, and future-proofs skills, ensuring a competitive edge in the design industry. Click here for more info: Website How to Book? 1-on-1 training. Customize your schedule from Mon to Sat from 9 am to 7 pm Call to book  Duration: 16 hours. Method: In-person or Live Online Sketchup and (Artificial Intelligence) Stable Diffusion Rendering Course (16 hours) Module 1: Sketchup Fundamentals (2 hours) Sketchup software overview and interface navigation Introduction to basic drawing tools and fundamental geometry creation techniques Module 2: Texturing and Material Mastery (2 hours) Application of textures and customization of materials Exploration of texture mapping and comprehensive material libraries Module 3: Illumination and Shadows (2 hours) Comprehending lighting principles and strategic light placement Crafting realistic shadows and reflections Module 4: Advanced Modeling Techniques (3 hours) Creating intricate shapes and harnessing advanced modeling tools Efficiently managing groups, components, and modifiers Module 5: Stable Diffusion Rendering (2 hours) Initiating stable diffusion rendering Optimizing rendering settings for superior outcomes Module 6: Scene Composition and Camera Configuration (2 hours) Exploring composition principles and camera perspectives Scene management and creation of captivating walkthrough animations Module 7: Rendering Optimization Strategies (2 hours) Techniques for optimizing models to expedite rendering Application of render passes and post-processing methods Module 8: Real-World Projects and Portfolio Building (1 hour) Application of acquired skills in completing authentic projects Professional portfolio presentation techniques Optional: Stable Diffusion and Python Installation (Additional 10 hours) Module 1: Introduction to Stable Diffusion and Python Comprehensive understanding of Stable Diffusion and Python's significance Module 2: System Prerequisites Hardware and software requirements for successful installation Module 3: Python Installation Guide Step-by-step installation process for various operating systems Module 4: Configuring Python Environment Configuration of environment variables and package managers Module 5: Stable Diffusion Installation Downloading and installing the Stable Diffusion package Module 6: Setting Up the Development Environment Configuration of integrated development environments (IDEs) for Python and Stable Diffusion Module 7: Troubleshooting and Common Issues Identification and resolution of common installation errors Module 8: Best Practices and Recommendations Effective management of Python and Stable Diffusion installations Module 9: Practical Applications and Projects Hands-on exercises exemplifying the practical usage of Stable Diffusion and Python Module 10: Advanced Topics (Optional) Exploration of advanced features and techniques Stable Diffusion https://stablediffusionweb.com https://stable-diffusion-ui.github.io https://stability.ai/stable-diffusion Upon successful completion of the Sketchup and Stable Diffusion Rendering Course with a focus on AI image rendering, participants will achieve the following: 1. Mastery of AI Image Rendering: Attain expertise in employing AI-powered rendering techniques to produce realistic and top-quality visualizations. 2. Proficiency in Sketchup for 3D Modeling: Navigate the software adeptly, utilize drawing tools with proficiency, and craft intricate 3D models. 3. Enhanced Rendering Optimization: Implement AI-based rendering to enhance model visuals, resulting in faster rendering times and superior image quality. 4. Application of AI-driven Lighting and Shadows: Employ AI algorithms for precise lighting placement, shadows, and reflections, elevating the realism of renderings. 5. Development of a Professional Portfolio: Present AI-rendered projects within a polished professional portfolio, highlighting advanced image rendering capabilities. 1. Mastering Sketchup: Attain proficiency in Sketchup, a renowned and user-friendly 3D modeling software, equipping you with the skills needed to adeptly create and manipulate 3D models. 2. Advanced Rendering Expertise: Explore stable diffusion rendering, an avant-garde technique that simplifies the creation of realistic and high-quality renderings. Broaden your rendering capabilities, producing visually stunning representations of your designs. 3. Practical Industry Applications: Cultivate practical skills relevant to diverse industries, encompassing architecture, interior design, product development, and visualization. Elevate your professional portfolio with captivating renderings that showcase your design prowess. 4. Interactive Learning: Participate in hands-on exercises and projects that promote active learning and the practical application of concepts. Benefit from personalized feedback and expert guidance, ensuring your continuous progress throughout the course. 5. Career Advancement: Elevate your career prospects by adding valuable skills to your toolkit. Proficiency in crafting detailed 3D models and impressive renderings through stable diffusion techniques opens doors to diverse job opportunities within the design and visualization sector. 6. Flexibility and Convenience: Access course materials online and learn at your own pace. Enjoy the flexibility of tailoring the coursework to your schedule, allowing you to harmonize your learning journey with other commitments. Course Advantages: Tailored Learning: Enjoy personalized 1-on-1 sessions, accommodating your schedule from Monday to Saturday, 9 am to 7 pm. Mastery of Sketchup: Develop proficiency in the widely-used and user-friendly 3D modeling software, enabling efficient creation and manipulation of 3D models. Advanced Rendering Proficiency: Acquire expertise in stable diffusion rendering for producing realistic, high-quality renderings that enhance the visual appeal of your designs. Practical Applicability: Develop practical skills applicable across diverse domains, including architecture, interior design, product development, and visualization, enriching your professional portfolio. Interactive Practical Experience: Engage in hands-on exercises with personalized guidance from seasoned instructors, ensuring consistent progress in your skillset. Career Progression: Boost your career opportunities by gaining valuable skills in 3D modeling and generating impressive renderings through stable diffusion techniques. Comprehensive Support: Benefit from free portfolio reviews, mock interviews, and career advice, providing additional resources to enhance your professional journey.

Thinking about learning Big Data? The BCS Foundation Award in Big Data teaches learners to understand how to manage Big Data and its use with Machine Learning.

Artificial Intelligence (AI) is the most disruptive technology since the internet came onto the scene. AI is transforming every aspect of how we manage projects from developing a business case, to planning the work, managing risk, and tracking performance. Because the technology and market are moving so fast, it can be difficult to know how to start using AI on projects. Generative AI for Project Management will engage you with diverse Generative AI tools to start, plan, and manage either your own project or a generic case study. We will embrace a tool agnostic approach to adopting, integrating, and scaling Generative AI without compromising data or trust. You will have hands-on practice utilizing AI tools to optimize your time and your outcomes. You will be accessing a variety of AI tools requiring you to register for a free account. A computer is required for all traditional classroom deliveries. None At the end of this program, you will be able to: Define essential terms and concepts related to artificial intelligence (AI) Illustrate how prompts facilitate interaction with Generative AI Recognize the capabilities of Large Language Models Craft prompts to develop project origination documents Create prompts to assist in planning a project Develop user stories with Generative AI Analyze project performance using Generative AI Identify the limitations of Generative AI Identify the risks associated with using Generative AI Articulate the need for governance and ethics when establishing an AI program in an organization Course Overview Getting Started Foundation Concepts Understanding essential terms and concepts related to AI Exploring various Generative AI Models Understanding Prompts Creating Prompts for Project Startup Prompts for starting a project Prompts for planning a project Best Practices for prompt engineering Creating Prompts for Managing Projects Creating agile user stories Measuring project performance Analyzing a schedule Using Generative AI Responsibly Limitations of AI Models Establishing an AI governance framework Future trends and next steps Summary and Next Steps

Thinking about learning more about how Artificial Intelligence can help in a business? The BCS Foundation Award - How AI Can Support Your Organisation explores the evolution of AI from its inception to present day, and identify potential future AI opportunities which exist to drive organisational strategy at all levels. It considers how AI can make improvements to processes, products and services, enabling an organisation to gain a competitive edge within the market, and the benefits and potential implications it has for the human workforce. You will learn the evolution of AI, an understanding of the shape and structure of organisations, an understanding of the role of AI in an organisation and an understanding of the art of the possible.