2436 Courses

Step confidently into a rewarding UK career with our transformative "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle. This bundle covers everything from honing your Python proficiency to crafting interactive web designs with HTML and CSS and developing dynamic applications using JavaScript. Uncover the secrets of Python's application in data science, machine learning, and neural networks. Establish a strong foundation in C# coding and exploring networking, GUI development, XML handling, and more. Delve into eight immersive CPD Accredited courses, each a standalone course: Course 01: The Complete Python 3 Course: Beginner to Advanced! Course 02: JavaScript for Everyone Course 03: HTML and CSS Coding: Beginner to Advanced Course 04: Basic C# Coding Course 05: Python Data Science with Numpy, Pandas and Matplotlib Course 06: Deep Learning & Neural Networks Python - Keras Course 07: Complete Python Machine Learning & Data Science Fundamentals Course 08: Python Programming Bible | Networking, GUI, Email, XML, CGI Our comprehensive Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensure you're well-prepared for diverse tech challenges. Elevate your UK career prospects with hands-on learning and real-world applications. Embrace the "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle for an all-encompassing skill set bound to make you a standout in the dynamic UK job landscape. Learning Outcomes Progress from beginner to advanced Python proficiency. Craft dynamic websites using HTML and CSS. Develop user-friendly web applications with JavaScript. Analyze data using Numpy, Pandas, and Matplotlib. Explore neural networks with Python's Keras. Gain practical machine learning expertise. Unleash your potential with our comprehensive Python Bootcamp: JavaScript, HTML & CSS Coding bundle that promises to transform your career trajectory. In the rapidly evolving tech landscape, Python proficiency stands as a cornerstone of success. From web development to data analysis and machine learning, Python is the language that opens doors to countless opportunities. Our Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensures you learn and master Python, securing your place at the forefront of innovation. Harness the expertise of excellent instructors who unravel the complexities of Python in a relatable and engaging manner. Dive into dynamic web design, crafting seamless interfaces with HTML and CSS, and building interactive web applications using JavaScript.Take the plunge into deep learning, understanding the intricacies of neural networks through Python's Keras library. As you progress, embrace the fundamental principles of machine learning, propelling your career to new heights. The time to seize the moment is now. The "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle equips you with indispensable skills, empowering you to stand out in a competitive job market. Whether a newcomer or a seasoned professional, this Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensures you're ready to conquer challenges and grasp opportunities. Embrace the power of Python today, and let it shape a future of endless possibilities. CPD 80 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Beginners to advanced learners. HTML, CSS, and JavaScript skills. Master Python programming. Numpy, Pandas, and data science. Diverse tech skill acquisition. Deep learning and machine learning Requirements Without any formal requirements, you can delightfully enrol in this course. Career path Web Developer: £25,000 - £50,000 Python Programmer: £30,000 - £60,000 Data Analyst: £25,000 - £45,000 Front-End Developer: £25,000 - £50,000 UI/UX Designer: £30,000 - £50,000 Machine Learning Engineer: £40,000 - £70,000 Full-Stack Developer: £35,000 - £60,000 Certificates CPD Certificate Of Completion Digital certificate - Included 8 Digital Certificates Are Included With This Bundle CPD Quality Standard Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript - £9.99

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***24 Hour Limited Time Flash Sale*** Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Immerse yourself in the world of Data Science, Machine Learning and Python with our exclusive bundle! Presenting eight thoughtfully curated courses, this bundle aims to enhance your understanding of intricate concepts. Within this collection, we proudly offer three QLS-endorsed courses: "2021 Data Science & Machine Learning with R from A-Z", "Excel Pivot Tables, Pivot Charts, Slicers, and Timelines", and "Machine Learning with Python", each complemented by a hardcopy certificate upon completion. Additionally, delve deeper with our five relevant CPD QS accredited courses. Explore Python Data Science with Numpy, Pandas, and Matplotlib. Uncover the secrets of R Programming for Data Science, enhance your statistical prowess with Statistics & Probability for Data Science & Machine Learning, and master spatial visualisation in Python. To top it all, there's a course on Google Data Studio for Data Analytics. Key Features of the Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Bundle: 3 QLS-Endorsed Courses: We proudly offer 3 QLS-endorsed courses within our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python bundle, providing you with industry-recognized qualifications. Plus, you'll receive a free hardcopy certificate for each of these courses. QLS Course 01: 2021 Data Science & Machine Learning with R from A-Z QLS Course 02: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines QLS Course 03: Machine Learning with Python 5 CPD QS Accredited Courses: Additionally, our bundle includes 5 relevant CPD QS accredited courses, ensuring that you stay up-to-date with the latest industry standards and practices. Course 01: Python Data Science with Numpy, Pandas and Matplotlib Course 02: R Programming for Data Science Course 03: Statistics & Probability for Data Science & Machine Learning Course 04: Spatial Data Visualisation and Machine Learning in Python Course 05: Google Data Studio: Data Analytics In Addition, you'll get Five Career Boosting Courses absolutely FREE with this Bundle. Course 01: Professional CV Writing Course 02: Job Search Skills Course 03: Self-Esteem & Confidence Building Course 04: Professional Diploma in Stress Management Course 05: Complete Communication Skills Master Class Convenient Online Learning: Our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python courses are accessible online, allowing you to learn at your own pace and from the comfort of your own home. Learning Outcomes: Master the usage of Excel Pivot Tables, Pivot Charts, Slicers, and Timelines. Develop proficiency in Machine Learning using Python. Acquire skills to manipulate data using Numpy, Pandas, and Matplotlib. Learn to code in R for Data Science applications. Understand the application of Statistics & Probability in Data Science & Machine Learning. Learn to create impactful data visualisations and analyse data using Google Data Studio. The "Data Science & Machine Learning, Excel Pivot & Machine Learning with Python" bundle is a comprehensive compilation designed to equip you with the theoretical knowledge necessary for the fast-evolving data-driven world. The three QLS-endorsed courses provide foundational understanding in Data Science, Machine Learning with R, Excel Pivot functionalities, and Machine Learning with Python, thereby setting a strong base. Furthermore, the five CPD QS accredited courses offer a deeper dive into the world of Data Science. Whether it is harnessing Python's power for data science tasks, exploring R programming, mastering statistical techniques, understanding spatial data visualisation in Python, or learning to navigate Google Data Studio for Data Analytics, this bundle has you covered. With this comprehensive learning experience, gain the theoretical insight needed to navigate and succeed in the dynamic field of data science. CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals interested in theoretical concepts of Data Science and Machine Learning. Professionals looking to enhance their knowledge in Excel Pivot Tables and Charts. Aspiring data scientists who want to learn Python and R programming for data science. Anyone seeking to understand data visualisation and analytics through Python and Google Data Studio. Career path Data Scientist: Leveraging data for actionable insights (£40,000 - £90,000 per annum). Machine Learning Engineer: Designing and implementing machine learning systems (£50,000 - £90,000 per annum). Excel Analyst: Using Excel for data analysis and visualisation (£30,000 - £60,000 per annum). Python Developer: Developing applications using Python (£40,000 - £80,000 per annum). Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included

Duration 4 Days 24 CPD hours This course is intended for While no prior programming or web development experience is required, target students should have good foundational computer skills. Overview Set up the tools and resources you need to perform Web Development. Create web pages in HTML, constructing valid, well-formed elements, including navigation links, sections, titles, and semantic markup. Enhance HTML content with tables, images, movies, and audio. Apply styles to HTML elements using CSS. Use CSS to format the edges, size, position, and layering of HTML elements. Apply complex style rules using advanced CSS selectors, including pseudo-class selectors, structural selectors, and pseudo-element selectors. Create complex layouts using CSS newspaper style columns, grid layouts, and flexible box layouts. Improve the quality of web content, including adaptability (different displays and devices), searchability, usability, and accessibility. Submit data through URL query strings and web forms for processing by a web application server. Write JavaScript code to make web pages more interactive, perform data processing tasks directly in the browser, and manipulate items in the current web page. Write JavaScript code to iterate through collections of elements in a page to get and set their attributes and add event listener code. Use third-party libraries and frameworks for web front-end development. Modern organizations depend heavily on the web to perform core business operations such as marketing, advertising, and selling products, providing services, and communicating with customers, partner organizations, and employees. Whatever you're creating on the web, HTML, CSS, and JavaScript? likely play an important role. These three languages provide the core toolkit for anyone looking to perform web development work. This course covers the fundamentals of web development using these three languages. Prerequisites This course assumes that students have strong experience working with computers. Previous experience programming in other languages is helpful, but not required for students to benefit from this course. Lesson 1: Setting Up Your Web Development Environment Topic A: Prepare Your Web Platform Topic B: Prepare Your Web Development Tools and Processes Topic C: Monitor the Web Request-Response Cycle Lesson 2: Creating Web Content in HTML Topic A: Create a Basic Web Page Topic B: Provide Navigation Links Between Web Pages Topic C: Improve Web Page Structure and Navigation Lesson 3: Adding Tables and Multimedia Content to a Web Page Topic A: Create a Table Topic B: Embed Images, Movies, and Audio in a Web Page Lesson 4: Applying Styles to Web Content Topic A: Apply Styles to HTML Topic B: Create a Style Sheet Topic C: Use Web Fonts Lesson 5: Controlling Edges, Size, and Position Topic A: Format Element Edges and Corners Topic B: Control an Element's Height and Width Topic C: Control an Element's Position and Layering Topic D: Normalize and Reset Browser CSS Defaults Lesson 6: Applying Complex Style Rules Topic A: Use Advanced Selectors Topic B: Manage User Interface States Topic C: Make Structure Apparent to Users Topic D: Use CSS Pseudo-Element Selectors Lesson 7: Creating Complex Layouts Topic A: Use CSS to Create Newspaper Style Columns Topic B: Use CSS to Create Grid Layouts Topic C: Use CSS to Create Flexible Box Layouts Lesson 8: Improving Web Content Topic A: Adjust the Layout for a Wide Variety of Devices Topic B: Perform Basic Search Engine Optimization Topic C: Test Your Website Lesson 9: Submitting Data to a Web Server for Processing Topic A: Submit Data Through a URL Topic B: Submit Data Through a Web Form Lesson 10: Writing JavaScript Code Topic A: Add JavaScript to a Web Page Topic B: Perform Operations on Data Topic C: Program Repetitive Tasks Topic D: Manipulate DOM Objects Lesson 11: Enumerating and Processing Collections of Elements Topic A: Enumerate Elements Topic B: Attach Events Through Code Lesson 12: Using Third-Party Libraries and Frameworks Topic A: Use a Third-Party JavaScript Library Topic B: Create a Web Page Based on a Third-Party Framework Additional course details: Nexus Humans Web Development with HTML5, CSS, and JavaScript (v1.0) 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 Web Development with HTML5, CSS, and JavaScript (v1.0) 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.

Level 6 Diploma (FREE QLS Endorsed Certificate) | 11 CPD Courses + 11 PDF Certificates | 255 CPD Points | CPD Accredited

SAFe® for Teams: In-House Training Build the skills needed to become a high-performing team member of an Agile Release Train (ART) and learn how to collaborate effectively with other teams by becoming a SAFe® 5 Practitioner (SP). During this course, you will gain an in-depth understanding of the ART, how it delivers value, and what you can do to effectively perform the role using Scrum, Kanban, and Extreme Programming (XP). You will also learn how to write stories and break down features, plan and execute iterations, and plan Program Increments. Finally, you'll learn about the continuous delivery pipeline and DevOps culture, how to effectively integrate with other teams in the program, and what it takes to continuously improve the train. What you will Learn To perform the role of a SAFe® Practitioner, you should be able to: Apply SAFe® to scale Lean and Agile development in their enterprise Know their team and its role on the Agile Release Train Know all other teams on the train, their roles, and the dependencies between the teams Plan Iterations Execute Iterations and demonstrate value Plan Program Increments Integrate and work with other teams on the train Introducing the Scaled Agile Framework® (SAFe®) Building an Agile Team Planning the Iteration Executing the Iteration Executing the Program Increment Practicing SAFe®

SAFe® for Teams Build the skills needed to become a high-performing team member of an Agile Release Train (ART) and learn how to collaborate effectively with other teams by becoming a SAFe® 5 Practitioner (SP). During this course, you will gain an in-depth understanding of the ART, how it delivers value, and what you can do to effectively perform the role using Scrum, Kanban, and Extreme Programming (XP). You will also learn how to write stories and break down features, plan and execute iterations, and plan Program Increments. Finally, you'll learn about the continuous delivery pipeline and DevOps culture, how to effectively integrate with other teams in the program, and what it takes to continuously improve the train. What you will Learn To perform the role of a SAFe® Practitioner, you should be able to: Apply SAFe® to scale Lean and Agile development in their enterprise Know their team and its role on the Agile Release Train Know all other teams on the train, their roles, and the dependencies between the teams Plan Iterations Execute Iterations and demonstrate value Plan Program Increments Integrate and work with other teams on the train Introducing the Scaled Agile Framework® (SAFe®) Building an Agile Team Planning the Iteration Executing the Iteration Executing the Program Increment Practicing SAFe®

In this course, students will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and by assembling and configuring an IoT device to work in a sensor network.

Kickstart your journey into deep learning and gain a strong understanding of deep neural networks through practical exercises. Develop your intuition and learn the fundamentals of artificial neural networks, activation functions, and loss functions. Gain practical experience with Python and TensorFlow 2.x, and apply your skills to build powerful deep learning models.

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.