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24 Hour Flash Deal **25-in-1 Robotics and Automation Engineering Mega Bundle** Robotics and Automation Engineering Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Robotics and Automation Engineering package online with Studyhub through our online learning platform. The Robotics and Automation Engineering bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Robotics and Automation Engineering course provides complete 360-degree training on Robotics and Automation Engineering. You'll get not one, not two, not three, but twenty-five Robotics and Automation Engineering courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Robotics and Automation Engineering courses are yours for as long as you want them once you enrol in this course This Robotics and Automation Engineering Bundle consists the following career oriented courses: Course 01: Robotics - Sensors Course 02: Advanced Arduino for Embedded Systems Course 03: Embedded Systems with 8051 Microcontroller Course 04: Machine Learning Basics Course 05: AutoCAD VBA Programming Course 06: Solidworks Foundation Training Course 07: 3D Modeling for 3D Printing Course 08: AutoCAD Programming using VB.NET with Windows Forms Course 09: Intermediate Solidworks Course Course 10: Learn PCB Printed Circuit Board Course 11: Digital Electric Circuits & Intelligent Electrical Devices Course 12: Electronic Device and Circuits Protection Training Course 13: Electronic & Electrical Devices Maintenance & Troubleshooting Course 14: CNC (Computer Numerical Control) Programming for Machining Course 15: Data Center Training Essentials: Mechanical & Cooling Course 16: Electricity - Theory and Safety Training Course 17: Power Electronics for Electrical Engineering Course 18: Electrical Power System and High Voltage Engineering Course 19: Electrical Engineering for Electrical Substations Course 20: Electric Vehicle Battery Management System Course 21: Engine Lubrication Systems Online Course Course 22: Manual Handling Training Course 23: Mechanical Engineering Course 24: MATLAB Simulink for Electrical Power Engineering Course 25: Solidworks Drawing Tools Training: Test Preparation The Robotics and Automation Engineering course has been prepared by focusing largely on Robotics and Automation Engineering career readiness. It has been designed by our Robotics and Automation Engineering specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners. The Robotics and Automation Engineering Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Robotics and Automation Engineering bundle course has been created with twenty-five premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Robotics and Automation Engineering Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Robotics and Automation Engineering Elementary modules, allowing our students to grasp each lesson quickly. 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Here's what you get: Step by step Robotics and Automation Engineering lessons One to one assistance from Robotics and Automation Engineeringprofessionals if you need it Innovative exams to test your knowledge after the Robotics and Automation Engineeringcourse 24/7 customer support should you encounter any hiccups Top-class learning portal Unlimited lifetime access to all twenty-five Robotics and Automation Engineering courses Digital Certificate, Transcript and student ID are all included in the price PDF certificate immediately after passing Original copies of your Robotics and Automation Engineering certificate and transcript on the next working day Easily learn the Robotics and Automation Engineering skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Robotics and Automation Engineering training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Robotics and Automation Engineering Requirements To participate in this Robotics and Automation Engineering course, all you need is - A smart device A secure internet connection And a keen interest in Robotics and Automation Engineering Career path You will be able to kickstart your Robotics and Automation Engineering career because this course includes various courses as a bonus. This Robotics and Automation Engineering is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Robotics and Automation Engineering career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free

This course aims to provide learners with a comprehensive understanding of the nature and process of Information Systems Development, Software Development Process, Programming Language, Globalization and the role of IT, Information Systems Ethics, Acceptable Use Policies, Intellectual Property, Privacy in Information Systems and future trends. After the successful completion of the course, you will be able to learn about the following, Understand the nature and process of Information Systems Development, its lifecycle, and Implementation Methodologies. Learn about Software Development Processes, models and technologies. Understand the nature, generations and types of Programming Language. Appreciate the concept of Globalization and the role of IT in Globalization. Learn about Information Systems Ethics and the Code of Ethics. Appreciate Acceptable Use Policies and Intellectual Property in IT. The concept of Privacy in Information Systems, its challenges and future trends. This course will provide learners with an understanding of the nature and process of Information Systems Development and Implementation Methodologies. The course will cover the Software Development Process, including models and technologies, and the nature, generations, and types of Programming Language. Learners will also learn about the role of IT in Globalization and the impact of Information Systems on the global economy. This course will provide learners with an understanding of the nature and process of Information Systems Development and Implementation Methodologies. The course will cover the Software Development Process, including models and technologies, and the nature, generations, and types of Programming Language. Learners will also learn about the role of IT in Globalization and the impact of Information Systems on the global economy. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Recognizing Information Systems Development and Globalisation Self-paced pre-recorded learning content on this topic. Recognizing Information Systems Development and Globalization Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. IT Professionals Software Developers Programmers Business Owners & Entrepreneurs Managers and Executives Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

CWISA training course description This CWISA course covers wireless technologies with reference to IoT. It examines from an IoT perspective how wireless works, and is an excellent introduction to IoT for the wireless engineer. Topics range from wireless technologies, RF, to mobile networks, IoT, and security. What will you learn Describe wireless networking and IoT technologies. Explain basic RF communications. Plan wireless solutions. Describe how to implement wireless solutions. Use best practices in implementing wireless solutions. CWISA training course details Who will benefit: Anyone working with IoT technologies. Prerequisites: RF fundamentals. Duration 4 days CWISA training course contents Introduction to wireless technologies History of wireless, radio waves and frequencies, wireless technologies and related components, common components of wireless solutions, LAN networking requirements, Network security, Implementing wireless solutions, staging, documentation, security updates, Industry organizations, IEEE, compatibility and certification groups. Wireless network use cases Wireless BANs, Wireless PANs, Wireless LANs, Wireless MANs, Wireless WANs, Wireless sensor networks, New network driver-Internet of Things, IoT for industry (IIoT), IoT for connected vehicles, Residential environments, Retail, Education (K12), Higher education, Agriculture, Smart cities / Public access, Health care, Office buildings, Hospitality, Industry, Stadiums, arenas, and large public venues. Planning wireless solutions Identifying use cases and applications, common wireless requirements and constraints, performing a wireless system design, selecting and evaluating design parameters. RF communications RF wave characteristics, RF propagation behaviours, RF signal metrics, fundamentals of wireless modulation. other wireless carriers, common frequency bands. Radio frequency hardware Hardware levels, basic RF hardware components (circuit board level), RF link types (use category). RF device types. Mobile communications networks Mobile networks, LTE, 5G, Use cases. Short-range, low-rate, and low-power networks RF and speed, RF and range, RF and power, 802.11, 802.15.4, Bluetooth, LoRa (Long range) / LoRaWAN, ZigBee, 6LoWPAN, NB-IoT and LTE-M. Wireless sensor networks What is a Wireless Sensor Network (WSN)? WSN applications, Sensors and actuators, WSN architectures, Planning a WSN. Internet of Things (IoT) Internet of Things (IoT) defined, IoT history and its definition revisited, one more comment on the definition of IoT, IoT verticals, Oil & Gas, IoT structure/ architecture basics, IoT connected objects. Securing wireless networks Confidentiality, integrity and availability, Privacy, non-repudiation, authenticity & safety, Importance of authentication in wireless networks, Key cryptographic technologies & concepts, Authentication methods, Authorisation, OAuth 2.0 authorisation framework, monitoring. Troubleshooting wireless solutions Proper solutions design, designing and implementing wireless solutions, basic installation procedures, general configuration considerations, troubleshooting and remediation, troubleshoot common problems in wireless solutions. Programming, scripting and automation What is an API? categories of APIs, common API communication methods, choosing a language, why are we integrating systems? Application & integration architectures. Data structures & types, XML, YAML, API types.

Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

This course is designed to help you understand the basic and advanced concepts of ethical hacking with ease. The course features interesting examples and coding activities in each video to keep you engaged and guides you effectively through writing programs to hack a system.

This is a comprehensive course designed to provide a solid foundation in web development principles and practices. This course is intentionally structured to provide a technical understanding of web development concepts without delving into intricate implementation details. Anyone looking to better understand how web applications are built can take 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. “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.

Learn to build a RESTful API using ASP.NET Core Minimal API, entity framework, and employ enterprise-level development practices and patterns. We will implement various support tools for data validations, logging, documentation, and security. You will learn everything you need to know about building a Minimal API using .NET 6 (or .NET 7 preview).

This course will help you to gain a mastery level understanding of the fundamentals of Android Studio, Android app development, and the Kotlin programming language by building six full-fledged applications as well as many more 'learning' applications throughout the course.