2439 Courses

***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.

Unity 3d face to face training customised and bespoke.

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.

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

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.

Description Register on the Hands on Programming on AutoCAD to Excel Using VB.NET today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Hands on Programming on AutoCAD to Excel Using VB.NET course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Section 01: Introduction Introduction - Hands on Programming on AutoCAD to Excel Using VB.NET 00:04:00 Who is this course for? - Hands on Programming on AutoCAD to Excel Using VB.NET 00:02:00 What will you learn from this course? - Hands on Programming on AutoCAD to Excel Using VB.NET 00:05:00 Tools needed 00:01:00 Course Prerequisites 00:04:00 Section 02: Exporting AutoCAD Objects to Excel Section Overview - Export AutoCAD Objects to Excel 00:02:00 Exporting Lines to Excel - Overview 00:02:00 Creating the VB.NET-Excel Project 00:06:00 Design of User Interface to Export Lines 00:10:00 Creating the Common Utility Class 00:19:00 Creating the ExportLines Method 00:12:00 Running and Testing ExportLines Method 00:06:00 Exporting MTexts to Excel - Overview 00:02:00 Creating the ExportMTexts Method 00:11:00 Export Polylines to Excel - Overview 00:01:00 Creating the ExportPolylines Method 00:12:00 Running and Testing ExportPoylines Method 00:12:00 Exporting Blocks (With Attributes) to Excel - Overview 00:02:00 Creating the ExportBlocks Method 00:12:00 Creating Export Blocks UI and Running the Code 00:06:00 Exporting Blocks (With Attributes) to Excel - Overview 00:02:00 Creating the User Interface for exporting Blocks to Excel 00:05:00 Creation of BlocksForm UI 00:04:00 Coding the BlocksForm Load Event 00:08:00 Testing the BlocksForm UI 00:03:00 Coding the BlocksForm to populate the Listboxes 00:15:00 Coding the BlocksForm Export Button 00:04:00 Coding the ExportBlocksWithAttributes Method 00:21:00 Running and Testing ExportBlocksWithAttributes Method 00:02:00 Section 03: Importing Excel File into AutoCAD Section Overview - Import Excel File into AutoCAD 00:01:00 Importing Lines from Excel File into AutoCAD - Overview 00:01:00 Creating ImportExcelUtil Class 00:02:00 Creating the ImportLines Method 00:19:00 Creating the UI for the ImportLines Method 00:02:00 Coding the ImportLines UI code behind. 00:07:00 Running and Testing ImportLines Method 00:08:00 Importing MTexts into AutoCAD - Overview 00:01:00 Creating the ImportMTexts Method 00:11:00 Creating ImportMTexts User Interface 00:02:00 Running and Testing ImportMTexts Method 00:02:00 Importing Polylines from Excel File into AutoCAD - Overview 00:01:00 Creating the ImportPolylines Method 00:14:00 Creating ImportPolylines User Interface 00:02:00 Running and Testing ImportPolylines Method 00:03:00 Importing Blocks (without Attributes) from Excel File into AutoCAD - Overview 00:01:00 Creating the ImportBlocks Method 00:09:00 Creating the ImportBlocks User Interface 00:02:00 Running and Testing ImportBlocks Method 00:03:00 Importing Blocks (with Attirubtes) from Excel File into AutoCAD - Overview 00:01:00 Creating the ImportBlocksWithAttributes Method 00:25:00 Creating the UI for ImportBlocksWithAttributes Method 00:04:00 Running and Testing ImportBlocksWithAttributes Method 00:03:00 Section 04: Exporting AutoCAD Objects to a File Exporting Lines to a File - Overview 00:02:00 Creating the ExportToFile Utility Class 00:04:00 Creating ExportLinesToFile Method 00:14:00 Creating the UI for ExportLinesToFile Method 00:08:00 Running and Testing ExportLinesToFile Method 00:02:00 Exporting MTexts to File - Overview 00:01:00 Creating the MTextToFile Method 00:06:00 Creating the UI for the ExportMTextToFile Method 00:01:00 Running and Testing ExportMTextToFile Method. 00:08:00 Exporting Polylines to File - Overview 00:02:00 Creating ExportPolylinesToFile Method 00:11:00 Exporting Polylines to File - User Interface 00:01:00 Running and Testing ExportPolylinesToFile Method 00:02:00 Exporting Blocks (without Attributes) to File - Overview 00:02:00 Creating the ExportBlocksToFile Method 00:11:00 Creating ExportBlocksToFile User Interface 00:02:00 Running and Testing ExportBlocksToFile Method 00:02:00 Exporting Blocks (With Attributes) to a File - Overview 00:02:00 Creating the EXportBlocksWithAttributesToFile Method 00:19:00 Creating the UI for ExportBlocksWithAttributesToFile Method 00:06:00 Coding the BlocksForm for ExportBlocksWithAttributeToFile Method 00:04:00 Running and Testing ExportBlocksWithAttributesToFile Method 00:03:00 Section 05: Importing Text File into AutoCAD Importing Text File into AutoCAD - Overview 00:01:00 Importing Lines from a Text File into AutoCAD - Overview 00:02:00 Creating the ImportFileUtil Class 00:01:00 Creating the ImportLinesMethod 00:17:00 Creation of ImportLines User Interface 00:03:00 Coding the ImportLines UI button 00:05:00 Running and Testing the ImportLines Method 00:04:00 Importing MTexts from Text File into AutoCAD - Overview 00:02:00 Creating the ImportMTexts Method 00:09:00 Creating the TextStyle Manipulation Code 00:02:00 Creating the UI for the ImportMTexts Method 00:01:00 Running and Testing the ImportMTexts Method 00:04:00 Importing Polylines from a Text File into AutoCAD - Overview 00:02:00 Creating the ImportPolylines Method 00:18:00 Creating the ImportPolylines UI 00:02:00 Running and Testing ImportPolylines (from a File) Method 00:02:00 Importing BLocks (without Attributes) from a Text File into AutoCAD - Overview 00:02:00 Creating the ImportBlocks (without Attributes) Method 00:15:00 Creating the ImportBlocks UI 00:05:00 Running and Testing ImportBlocks (without Attributes) Method 00:04:00 Importing Blocks (with Attributes) from a Text File into AutoCAD - Overview 00:02:00 Creating the ImportBlocksWithAttributes from a File Method 00:24:00 Creating the ImportBlocksWithAttributes (from a File) UI (Part 1) 00:06:00 Creating the ImportBlocksWithAttributes (from a File) UI (Part 2) 00:04:00 Running and Testing ImportBlocksWithAttributes (from a File) Method 00:03:00

Step into the world of data analysis and gain practical experience analyzing real-world datasets with the help of this course. This course will not only guide you in analyzing data efficiently in Python from scratch but also help you in conducting your own analysis with Python and extracting valuable insights that can transform your business!

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.

SAFe® for Teams: Virtual 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®