505 Programmer courses

Step into the fascinating world of deep learning with our Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course. This course takes you through the power of neural networks by using one of the most iconic machine learning challenges—digit recognition. Whether you're brushing up on your AI knowledge or taking your first step into neural networks, this course simplifies the complexity without watering it down. Expect clear, jargon-free explanations that give neural networks a human touch. Learn how digits are recognised, how machines learn from data, and what goes on inside those layers of artificial intelligence—without sounding like a maths textbook. From data input to prediction output, the entire pipeline is broken down in a logical, structured, and thoroughly digestible way. If you're into machine learning, this project will speak your language—digitally. Learning Outcomes: Gain a solid understanding of the principles of deep learning and neural networks. Learn how to use Google Collab to import and preprocess data for deep learning projects. Discover how to create your own neural network model to recognise handwritten digits. Understand how to train your model, make predictions, and evaluate its performance. Learn how to create your own convolutional neural network model for even more advanced recognition tasks. The Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network for handwritten digit recognition. Using Google Collab, you'll learn how to import and preprocess data for deep learning projects, create your own neural network model, and train it to recognize handwritten digits with high accuracy. You'll also discover how to evaluate the performance of your model and create a convolutional neural network model for even more advanced recognition tasks. Deep Learning Projects - Handwritten Digit Recognition Using Neural Network Course Curriculum Lesson 01: Introduction to Project Lesson 02: Google Collab Lesson 03: Importing Packages and Data Lesson 04: Preprocessing and Model Creation Lesson 05: Training the Model and Prediction Lesson 06: Model Creation using CNN Lesson 07: CNN Model Prediction How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and neural networks. Programmers who want to learn how to build their own neural network models for advanced recognition tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of deep learning and neural networks. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Software Engineer: £28,000 - £60,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Ever wondered how machines recognise faces, detect traffic signs, or even tag photos with uncanny accuracy? This course dives straight into the heart of Convolutional Neural Networks (CNNs) – the very engine behind image recognition and deep learning breakthroughs. With a clear focus on project-based learning, you’ll explore how CNNs work, how they’re built, and how they’re trained to see and interpret the world digitally. The content flows logically and stays rooted in clarity, making even the most complex architectures feel almost polite. This is not just a sequence of slides and jargon. It’s a well-structured digital journey tailored for learners who want to confidently grasp how deep learning models behave and evolve. Whether you're brushing up on your neural network knowledge or aiming to reinforce your AI expertise, the course serves up algorithms, code walkthroughs and layered insights with a tone that’s informative, direct, and occasionally dry-witted. If you fancy turning raw data into pixel-level predictions using nothing but code, logic, and neural layers — you’re exactly where you need to be. Learning Outcomes: Gain a solid understanding of convolutional neural networks and their applications in deep learning. Learn how to install the necessary packages and set up a dataset structure for deep learning projects. Discover how to create your own convolutional neural network model and layers using Python. Understand how to preprocess and augment data for advanced image recognition tasks. Learn how to evaluate the accuracy of your models and understand the different models available for deep learning projects. The Deep Learning Projects - Convolutional Neural Network course is designed to provide you with the skills and knowledge you need to build your own advanced deep learning projects. Using Python, you'll learn how to install the necessary packages, set up a dataset structure, and create your own convolutional neural network model and layers. You'll also learn how to preprocess and augment data to enhance the accuracy of your models and evaluate the performance of your models using data generators. Deep Learning Projects - Convolutional Neural Network Course Curriculum Section 01: Introduction Section 02: Installations Section 03: Getting Started Section 04: Accuracy How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and convolutional neural networks. Programmers who want to learn how to build advanced models for image recognition. Entrepreneurs who want to develop their own deep learning-based applications for image recognition. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of convolutional neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Computer Vision Engineer: £30,000 - £70,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Step into the intricate world of artificial neural networks with a course that sheds light on one of the most dynamic branches of deep learning. Designed for those keen to explore the structure, function and logic behind intelligent systems, this course blends academic insight with a clear, structured approach to the evolving digital frontier. From perceptrons to multilayer networks, it offers a layered understanding of how machines mimic the human brain’s decision-making process — minus the caffeine and existential crises. Whether you're sharpening your knowledge or stepping into the field with curiosity, this course provides a sharp focus on the core principles that power technologies like image recognition, voice synthesis and predictive modelling. Delivered in an accessible format, it caters to learners who want depth without the fluff, logic without the waffle, and progress without the guesswork. Neural networks may be artificial — but your understanding of them won’t be. Learning Outcomes: Gain a solid understanding of artificial neural networks and their applications in deep learning. Learn how to install the necessary packages and preprocess data for neural network training. Discover how to encode data and build your own artificial neural network using Python. Understand the steps involved in making predictions using your neural network model. Learn how to deal with imbalanced data in your neural network training. The Project on Deep Learning - Artificial Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network and perform complex tasks using deep learning. You'll learn how to install the necessary packages, preprocess data, and encode data for neural network training. You'll also gain a deeper understanding of artificial neural networks and learn how to build your own model using Python. By the end of the course, you'll be able to make predictions using your neural network model and understand how to deal with imbalanced data in your training. Project on Deep Learning - Artificial Neural Network Course Curriculum Section 01: Introduction Section 02: ANN Installation Section 03: Data Preprocessing Section 04: Data Encoding Section 05: Steps to Build ANN Section 06: Predictions and Imbalance-Learn How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and artificial neural networks. Programmers who want to learn how to build their own neural network models for advanced tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of artificial neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Deep Learning Engineer: £30,000 - £75,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Ever wondered how to speak confidently about buildings, materials, and construction terms—in Portuguese? This course is your blueprint to building language skills tailored to the world of structural design and architecture. From concrete columns to roofing terms, you'll learn how to talk structures with precision and clarity—all in Portuguese. Whether you're a construction enthusiast, a professional working with Portuguese-speaking clients, or simply keen to expand your vocabulary, this course is structured to help you build fluency without ever picking up a hammer. Expect engaging modules that introduce you to the foundations of structural language—from everyday construction phrases to technical expressions. It's not about laying bricks; it's about laying down words that matter. Delivered entirely online, this course offers you the flexibility to learn from wherever you are, while gaining knowledge that’s both specific and linguistically sharp. If structure speaks to you, let it speak Portuguese too. Learning Outcomes: Gain a solid understanding of artificial neural networks and their applications in deep learning. Learn how to install the necessary packages and preprocess data for neural network training. Discover how to encode data and build your own artificial neural network using Python. Understand the steps involved in making predictions using your neural network model. Learn how to deal with imbalanced data in your neural network training. The Project on Deep Learning - Artificial Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network and perform complex tasks using deep learning. You'll learn how to install the necessary packages, preprocess data, and encode data for neural network training. You'll also gain a deeper understanding of artificial neural networks and learn how to build your own model using Python. By the end of the course, you'll be able to make predictions using your neural network model and understand how to deal with imbalanced data in your training. Build Structures in Portuguese Course Curriculum Introduction Section 01: Chapter 1 Section 02: Chapter 2 Section 03: Chapter 3 Section 04: Chapter 4 Section 05: Chapter 5 Section 06: Chapter 6 Section 07: Chapter 7 Section 08: Chapter 8 Section 09: Chapter 9 Section 10: Chapter 10 How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and artificial neural networks. Programmers who want to learn how to build their own neural network models for advanced tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of artificial neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Deep Learning Engineer: £30,000 - £75,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Dive into the intricate world of deep learning with this sharply focused course on heuristic techniques using R. This programme is designed for learners keen to understand how heuristics shape machine learning models, particularly in deep neural networks. Whether you're brushing up on your algorithmic intuition or delving deeper into optimisation patterns, this course delivers a solid framework rooted in logic, not lingo. With R as your analytical companion, you'll explore neural computation, gradient-based strategies, backpropagation nuances, and heuristic-inspired adjustments that enhance model efficiency. This isn't about flashy tools or inflated claims — it's about getting your mind around how deep learning truly works, one clever calculation at a time. No fluff, no filler — just clear insights and well-paced learning to support your journey through the matrix of machine intelligence. Learning Outcomes: Develop an understanding of experimental design and how it applies to heuristics. Learn how to apply heuristics to real-world problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Understand how to use R programming language for deep learning heuristics. Develop skills in analyzing data sets and creating predictive models. Learn how to implement different heuristics algorithms in R programming. The Essential Training on Deep Learning Heuristic using R is designed to provide students with a comprehensive understanding of heuristics and how they can be applied to various real-world problems. The course covers experimental design, data analysis, and predictive modelling using R programming language. Students will learn about different heuristics algorithms and how to implement them in R to solve complex problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Throughout the course, students will work on various projects that will help them develop practical skills in analyzing data sets and creating predictive models. They will learn how to design experiments, collect and analyse data, and create models that can be used to make predictions. By the end of the course, students will have a strong understanding of heuristics, and deep learning, and how to apply them to solve real-world problems. Essential Training on Deep Learning Heuristic using R Course Curriculum Section 01: Experimental Design - Heuristics Project 1-Agriculture Section 02: Experimental Design - Heuristics Project 2-Cryptocurrencies Section 03: Experimental Design: Heuristics Project 3-Energy Sector Section 04: Experimental Design: Heuristics Project 4-Financial Markets How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data scientists who want to learn how to apply deep learning heuristics to solve real-world problems. Programmers who want to learn R programming language for data analysis and predictive modeling. Professionals in the agriculture, cryptocurrency, energy, and financial markets sectors who want to apply heuristics to solve complex problems. Students who want to learn about deep learning heuristics and how they can be applied to real-world problems. Anyone interested in developing practical skills in data analysis and predictive modelling using R programming language. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Deep Learning Engineer: £30,000 - £90,000 AI Researcher: £40,000 - £120,000 Data Scientist: £35,000 - £90,000 Machine Learning Engineer: £40,000 - £100,000 AI Architect: £50,000 - £150,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

The Ultimate Dot Net Training for Everyone Course is designed to elevate your programming prowess with a clear, well-organised approach to mastering the .NET framework. Whether you’re a complete beginner or looking to sharpen your coding talents, this course presents a logical progression through essential concepts and advanced techniques, ensuring a smooth learning journey. With an emphasis on clarity and precision, you’ll gain confidence in developing applications using the latest Microsoft technologies, all at your own pace and convenience. Forget the jargon and unnecessary fluff—this course offers focused lessons packed with relevant examples and insightful explanations that make complex topics approachable and even enjoyable. Dive into the world of .NET and discover how to create efficient, robust software solutions without the fuss. Ideal for aspiring developers and tech enthusiasts alike, this training is your trusted companion for unlocking the full potential of the .NET platform—no travel, no fuss, just pure learning delivered straight to your screen. Learning Outcomes: Gain a solid understanding of the .NET framework and its capabilities. Learn how to program in C# and create basic software applications. Discover how to handle exceptions, work with databases, and create games and chatbots. Understand the principles of object-oriented programming and their applications in software development. Learn how to create robust and scalable software applications using the .NET framework. The Ultimate Dot Net Training for Everyone course is designed to provide you with the skills and knowledge you need to become a proficient .NET software developer. Starting with the basics of C# programming and moving on to more advanced topics, this course covers everything you need to know to create robust and scalable software applications. You'll learn how to work with databases, handle exceptions, and even create your own games and chatbots. Along the way, you'll gain a solid understanding of the principles of object-oriented programming and its applications in software development. Ultimate Dot Net Training for Everyone Course Curriculum Section 01: Installation Section 02: Basics on C# Programming Section 03: Conditional Constructs Section 04: Loops Section 05: Arrays and For loop Section 06: Methods Section 07: OOPS Concepts Section 08: Project - Creating a Login Page Section 09: File Handling Section 10: Exception Handling Section 11: Database Connectivity Section 12: Project - Creating a login Page Using DB Connectivity Section 13: Working with Database Section 14: Project - Flappy Bird Game Section 15: Project - Baneful Game Section 16: Project - Chabot Section 17: Project - Online Examination System How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals who are new to programming and want to learn about the .NET framework. Experienced programmers who want to expand their skills and knowledge in .NET development. Entrepreneurs who want to develop their own software applications using .NET. Students who want to enhance their skills in software development and prepare for a career in the field. Anyone who wants to develop their skills in the software development industry. Career path Junior .NET Developer: £20,000 - £35,000 .NET Developer: £28,000 - £55,000 Senior .NET Developer: £40,000 - £80,000 Software Engineer: £28,000 - £60,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of C++ and object-oriented programming concepts. This course is for Non-Developers, or anyone who wants to have a basic understanding of and learn how to code C++ applications and syntax Overview Companies are constantly challenged to keep their applications, development projects, products, services (and programmers!) up to speed with the latest industry tools, skills, technologies and practices to stay ahead in the ever-shifting markets that make up today's fiercely competitive business landscape. The need for application, web and mobile developers and coders is seemingly endless as technologies regularly change and grow to meet the modern needs of demanding industries and clients. C++ and Programming Basics for Non-Programmers is a five-day, basic-level training course geared for IT candidates who have little or no prior experience in computer programming. Throughout this gentle introduction to programming and C++, students will learn to create applications and libraries using C++ using best practices and sound OO development techniques for writing object-oriented programs in C++. Special emphasis is placed on object-oriented concepts and best practices throughout the training. Fundamentals of the Program Development Cycle Computer Architecture The Notion of Algorithms Source Code vs. Machine Code Compile-Time vs. Run-Time Software Program Architecture Standalone Client/Server Distributed Web-Enabled IDE (Interactive Development Environment) Concepts Looping Constructs Counter-Controlled Repetition Sentinel-Controlled Repetition Nested Control Constructs break and continue Statements Structured Programming Best Practices Writing Methods (Functions) Static vs. Dynamic Allocation Declaring Methods Declaring Methods with Multiple Parameters Method-Call Stack Scope of Declarations Argument Promotion and Casting Designing Methods for Reusability Method Overloading Arrays Purpose of Arrays Declaring and Instantiating Arrays Passing Arrays to Methods Multidimensional Arrays Variable-Length Argument Lists Using Command-Line Arguments Using Environment Variables Deeper Into Classes and Objects Controlling Access to Class Members Referencing the Current Object Using this Overloading Constructors Default and No-Argument Constructors Composition of Classes Garbage Collection and Destructors The finalize Method Static Class Members Defining Classes Using Inheritance Application Development Fundamentals Structure of a C++ Program Memory Concepts Fundamental Data Type Declarations Fundamental I/O Concepts Fundamental Operators Arithmetic Operators Logical Operators Precedence and Associativity Building and Deploying a C++ Program Superclasses and Subclasses Advantages of Using Inheritance protected Class Members Constructors in Subclasses Increasing Convenience by Using Polymorphism Purpose of Polymorphic Behavior The Concept of a Signature Abstract Classes and Methods final Methods and Classes Purpose of Interfaces Using and Creating Interfaces Common Interfaces of the C++ API Files and Streams Concept of a Stream Class File Sequential Access Object Serialization to/from Sequential Access Files Fundamental Searching and Sorting Introduction to Searching Algorithms Linear Search Binary Search Introduction to Sorting Algorithms Selection Sort Insertion Sort Merge Sort Fundamental Data Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees Exception Handling Types of Exceptions Exception Handling Overview Introduction to Classes and Objects Classes, Objects and Methods Object Instances Declaring and Instantiating a C++ Object Declaring Methods set and get Methods Initiating Objects with Constructors Primitive Types vs. Reference Types Flow Control Conditional Constructs Exception Class Hierarchy Extending Exception Classes When to Throw or Assert Exceptions Formatted Output printf Syntax Conversion Characters Specifying Field Width and Precision Using Flags to Alter Appearance Printing Literals and Escape Sequences Formatting Output with Class Formatter Strings, Characters and Regular Expressions Fundamentals of Characters and Strings String Class String Operations StringBuilder Class Character Class StringTokenizer Class Regular Expressions Regular Expression Syntax Pattern Class Matcher Class Fundamental GUI Programming Concepts Overview of Swing Components Displaying Text and Graphics in a Window Event Handling with Nested Classes GUI Event Types and Listener Interfaces Mouse Event Handling Layout Managers Additional course details: Nexus Humans C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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 C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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.

The Python Mini Bundle offers a clean, structured pathway into essential programming languages and web design basics. Whether you're wrestling with loops or wondering what exactly Go Lang does with its semicolons, this bundle provides clarity across popular technologies—without sounding like a lecture from a sleep-deprived engineer. It starts with Python’s logic, adds HTML and CSS for structure and style, sprinkles in data analysis, and rounds it out with Go Lang—because sometimes, even programmers enjoy a change of pace. It's ideal for learners who enjoy seeing code behave (most of the time) and data that tells a story without emotional outbursts. Learning Outcomes: Understand Python syntax, loops, and structured programming logic. Learn Go Lang structures and execution models for simple programmes. Explore HTML basics and webpage layout fundamentals. Study CSS styling for visual structure and site presentation. Apply Python to explore introductory data analysis techniques. Identify core programming patterns across language types. Who is this Course For: Beginners curious about Python and clean programming logic. Students exploring front-end and back-end web structure theory. Individuals interested in combining coding with data storytelling. Learners wanting to explore multiple programming language basics. Aspiring analysts looking at foundational coding for data handling. Developers transitioning to structured web and code learning. Hobbyists keen to write functional, logical, readable code. Coders who appreciate both syntax and simplicity in language. Career Path: Python Developer – £45,000/year Junior Data Analyst – £30,000/year Web Developer (HTML/CSS) – £32,000/year Go Lang Developer – £48,000/year Software Tester – £34,000/year Front-End Developer – £35,500/year

Duration 4 Days 24 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Network administrators Solutions designers System installers System integrators System administrators Overview After completing this course, you should be able to: Explain the transactional service activation and how it relates to business requirements Explain how Cisco NSO communicates with network devices Understand the NETCONF protocol and be able to read and write simple YANG models Understand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capable Understand the support for candidate configuration and confirmed commit support Use logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devices Explain the YANG service model structure Design a real-world usable service Explain the mapping logic of service parameters to device models and consequently to device configurations Describe the use of different integration options and APIs Explain how to implement action with use of config-templates in NSO package Explain the use of Reactive FASTMAP in for manipulating and implementing advanced NFV components Describe the use of feature components and function packs Define and explain the ETSI MANO principles and solution Work with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures Describe Cisco NSO 5.3 new features and changes in NSO The NSO Essentials for Programmers and Network Architects (NSO201) v4.1 course introduces you to Cisco Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides an overview of NSO as a network automation solution as well as introducing you to NETCONF, YANG, and XPath. You will learn about managing devices and creating device templates, service management and service package creation, network element drivers, interfacing with other systems using APIs, configuring and troubleshooting system settings, managing alarms and reporting, configuring NSO for scalability and performance, and capabilities that can be added to Cisco NSO. Course Outline Introducing Service Orchestration with Cisco NSO Exploring Cisco NSO Architecture Orchestrating Network Solutions Describing Cisco NSO Operation Installing Cisco NSO Exploring the Advantages of NETCONF Managing Devices Using the Device Manager Creating YANG Models Using Services Implementing Services with Model-to-Model Mapping Designing Services in Cisco NSO Managing the Service Lifecycle Programming with Python in Cisco NSO Configuring and Troubleshooting System Settings Discovering Cisco NSO Northbound APIs Managing Alarms and Reporting Configuring Cisco NSO for Scalability and Performance Describing Cisco NSO VNF Manager and Function Packs

Duration 4 Days 24 CPD hours This course is intended for System installersSystem integratorsSystem administratorsNetwork administratorsSolutions designers Overview After completing this course, you should be able to:Explain transactional service activation and how it relates to business requirementsExplain the benefits and uses of Cisco NSOExplain how Cisco NSO communicates with network devicesUnderstand the NETCONF protocol and be able to read and write simple YANG modelsInstall NSO and describe how NSO uses NETCONF and the Device Manager componentUnderstand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capableExplain the YANG service model structureDescribe how YANG is used with NSO, create and deploy a service, and explain NSO FASTMAPDesign and manage services with YANG modelsPerform NSO configuration and basic troubleshooting, and describe the following NSO features: integration options, alarms and reporting, scalability and performance options, and available function packsUse logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devicesExplain the mapping logic of service parameters to device models and consequently to device configurationsDescribe the use of different integration options and APIsExplain the use of Reactive FASTMAP for manipulating and implementing advanced Network Functions Virtualization (NFV) componentsDescribe the use of feature components and function packsDefine and explain the European Telecommunications Standards Institute (ETSI) Open Source NFV Management and Orchestration (MANO) principles and solutionWork with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures The Cisco NSO Essentials for Programmers and Network Architects (NSO201) course introduces you to Cisco© Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides a brief overview of NSO as a network automation solution, as well as an introduction to NETCONF, YANG, and XPath. You will learn about service packages, network element drivers, and Application Programming Interfaces (APIs). The course also covers service creation, device and configuration management, NSO maintenance, NSO options and integrations, and basic NSO troubleshooting. Introduction to Cisco NSO Meeting Challenges with Orchestration Challenges of Network Management Challenges of Network Orchestration NSO Features and Benefits That Meet Challenges Standardized Approach What Is NSO? Logical Architecture Components What Does NSO Do? Orchestration Use Cases How Does NSO Work? Introduction to NETCONF and YANG Packages Mapping Logic Network Element Drivers (NEDs) Resources and Training Resources Training Get Started with Cisco NSO Installing Cisco NSO Setup Overview Cisco NSO Local Installation Installing NEDs Using NetSim NETCONF Overview Challenges of Network Management Introduction to NETCONF NETCONF Operation Device Manager Device Manager Overview Device Configuration Management Device Connection Management Templates and Groups Other Device Management Tools Service Manager Essentials YANG Overview Introduction to YANG Other Representations of YANG Data Types XPath Overview Basic YANG Statements Can You Spot the Error? Using Services Package Architecture Creating a Service Package Sample Service Configuration Service Template YANG Service Model Deploying a Service Model-to-Model Mapping Mapping Introduction Mapping Logic FASTMAP Template Processing Service Design and Cisco NSO Programmability Service Design Service Design Overview Top-Down Approach Bottom-Up Approach Device Configuration Service Model Service Management Service Management Tasks Service Lifecycle Management Guidelines NSO Programmability Introduction NSO Programmability Overview Python Service Skeleton Creating a Service YANG Model Creating a Service Template Template Processing with Python Cisco NSO Flexibility System Configuration and Troubleshooting System Configuration System Troubleshooting Integration Integration Options NETCONF Server Web Integration SNMP Agent Alarm Management and Reporting Alarm Management Reporting Scalability and Performance High Availability High-Availability Cluster Communications Clustering Layered Service Architecture Addressing Performance Limitations Components and Function Packs Function Packs NFV Orchestration Reactive FASTMAP