347 Scala courses

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient, maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects, adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. INTRODUCTION TO SCALA * Scala features and benefits * Comparing Scala with Java and other OO languages * Installing Scala and setting up the development environment OBJECT-ORIENTED PROGRAMMING IN SCALA * Classes and objects * Traits, mixins, and inheritance * Companion objects and factories * Encapsulation and polymorphism FUNCTIONAL PROGRAMMING BASICS * Pure functions and referential transparency * Higher-order functions and currying * Immutability and persistent data structures * Pattern matching and recursion HAVING FUN WITH FUNCTIONAL DATA STRUCTURES * Lists, sets, and maps in Scala * Folding and reducing operations * Stream processing and lazy evaluation * For-comprehensions BUILDING WEB APPLICATIONS IN FUNCTIONAL STYLE * Introduction to Play Framework * Functional web routing and request handling * JSON handling with Play-JSON Middleware and functional composition CONNECTING TO A DATABASE * Introduction to Slick library * Database configuration and setup * Querying and updating with Slick * Transactions and error handling BUILDING SCALABLE AND EXTENSIBLE COMPONENTS * Modular architecture and design patterns * Dependency injection with MacWire * Type classes and type-level programming * Implicit parameters and conversions CONCURRENCY PROGRAMMING & AKKA * Introduction to Akka framework and Actor model * Actor systems and message passing * Futures and Promises * Supervision and fault tolerance BUILDING CONFIDENCE WITH TESTING * Introduction to ScalaTest and ScalaCheck * Unit testing and property-based testing * Test-driven development in Scala * Mocking and integration testing INTEROPERABILITY BETWEEN SCALA AND JAVA * Calling Java code from Scala * Using Java libraries in Scala projects * Converting Java collections to Scala collections * Writing Scala code that can be called from Java USING GENERATIVE AI AND GPT TECHNOLOGIES IN SCALA PROGRAMMING * Overview of GPT and generative AI * Integrating GPT with Scala applications * Use cases and practical examples ADDITIONAL COURSE DETAILS: Nexus Humans Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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.

Learn the process to design and develop big data engineering projects using Apache Spark. This example-driven advanced-level course will help you understand real-time stream processing using Apache Spark and you can apply that knowledge to build real-time stream processing solutions.

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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. INTRODUCTION TO MACHINE * Learning and Scala * Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. * What is Machine Learning? * Machine Learning with Scala: Advantages and Use Cases SUPERVISED LEARNING IN SCALA * Learn the basics of supervised learning and how to apply it using Scala. * Supervised Learning: Regression and Classification * Linear Regression in Scala * Logistic Regression in Scala UNSUPERVISED LEARNING IN SCALA * Understand unsupervised learning and how to apply it using Scala. * Unsupervised Learning:Clustering and Dimensionality Reduction * K-means Clustering in Scala * Principal Component Analysis in Scala NEURAL NETWORKS AND DEEP LEARNING IN SCALA * Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. * Introduction to Neural Networks * Feedforward Neural Networks in Scala * Deep Learning and Convolutional Neural Networks INTRODUCTION TO GENERATIVE AI AND GPT IN SCALA * Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. * Generative AI: Overview and Use Cases * Introduction to GPT (Generative Pre-trained Transformer) * GPT-Scala: A Library for GPT in Scala REINFORCEMENT LEARNING IN SCALA * Understand the basics of reinforcement learning and its implementation in Scala. * Introduction to Reinforcement Learning * Q-learning and Value Iteration * Reinforcement Learning with Scala TIME SERIES ANALYSIS USING SCALA * Learn time series analysis techniques and how to apply them in Scala. * Introduction to Time Series Analysis * Autoregressive Integrated Moving Average (ARIMA) Models * Time Series Analysis in Scala NATURAL LANGUAGE PROCESSING (NLP) WITH SCALA * Gain an understanding of natural language processing techniques and their application in Scala. * Introduction to NLP: Techniques and Applications * Text Processing and Feature Extraction * NLP Libraries and Tools for Scala IMAGE PROCESSING AND COMPUTER VISION WITH SCALA * Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. * Introduction to Image Processing and Computer Vision * Feature Extraction and Image Classification * Image Processing Libraries for Scala MODEL EVALUATION AND VALIDATION * Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. * Model Evaluation Metrics * Cross-Validation Techniques * Model Selection and Tuning in Scala SCALABLE MACHINE LEARNING WITH SCALA * Learn how to handle large-scale machine learning problems using Scala. * Challenges of Large-Scale Machine Learning * Data Partitioning and Parallelization * Distributed Machine Learning with Scala MACHINE LEARNING DEPLOYMENT AND PRODUCTION * Understand the process of deploying machine learning models into production using Scala. * Deployment Challenges and Best Practices * Model Serialization and Deserialization * Monitoring and Updating Models in Production ENSEMBLE LEARNING TECHNIQUES IN SCALA * Discover ensemble learning techniques and their implementation in Scala. * Introduction to Ensemble Learning * Bagging and Boosting Techniques * Implementing Ensemble Models in Scala FEATURE ENGINEERING FOR MACHINE LEARNING IN SCALA * Learn advanced feature engineering techniques to improve machine learning model performance in Scala. * Importance of Feature Engineering in Machine Learning * Feature Scaling and Normalization Techniques * Handling Missing Data and Categorical Features ADVANCED OPTIMIZATION TECHNIQUES FOR MACHINE LEARNING * Understand advanced optimization techniques for machine learning models and their application in Scala. * Gradient Descent and Variants * Regularization Techniques (L1 and L2) * Hyperparameter Tuning Strategies

Duration 1 Days 6 CPD hours This course is intended for This course is designed for candidates looking to demonstrate foundational-level knowledge of cloud-based solutions to facilitate productivity and collaboration on-site, at home, or a combination of both.ÿCandidates may have knowledge of cloud-based solutions or may be new to Microsoft 365. Overview After completing this course, students will be able to: Describe cloud concepts Describe core Microsoft 365 services and concepts Describe security, compliance, privacy, and trust in Microsoft 365 Describe Microsoft 365 pricing and support This course introduces Microsoft 365, an integrated cloud platform that delivers industry-leading productivity apps along with intelligent cloud services, and world-class security. You?ll learn foundational knowledge on the considerations and benefits of adopting cloud services and the Software as a Service (SaaS) cloud model, with a specific focus on Microsoft 365 cloud service offerings. You will begin by learning about cloud fundamentals, including an overview of cloud computing. You will be introduced to Microsoft 365 and learn how Microsoft 365 solutions improve productivity, facilitate collaboration, and optimize communications. The course then analyzes how security, compliance, privacy, and trust are handled in Microsoft 365, and it concludes with a review of Microsoft 365 subscriptions, licenses, billing, and support. 1 - DESCRIBE CLOUD COMPUTING * What is cloud computing * Describe the shared responsibility model * Define cloud models * Describe the consumption-based model 2 - DESCRIBE THE BENEFITS OF USING CLOUD SERVICES * Describe the benefits of high availability and scalability in the cloud * Describe the benefits of reliability and predictability in the cloud * Describe the benefits of security and governance in the cloud * Describe the benefits of manageability in the cloud 3 - DESCRIBE CLOUD SERVICE TYPES * Describe Infrastructure as a Service * Describe Platform as a Service * Describe Software as a Service 4 - WHAT IS MICROSOFT 365? * Describe the differences between Office 365 and Microsoft 365 * Describe Windows 365 * Describe how Microsoft 365 empowers workers in this hybrid world of work * Explore Microsoft 365 tenant 5 - DESCRIBE PRODUCTIVITY SOLUTIONS OF MICROSOFT 365 * Describe the productivity capabilities and benefits of Microsoft 365 * Describe Microsoft 365 Apps * Describe work management tools in Microsoft 365 * Describe additional Microsoft 365 productivity apps 6 - DESCRIBE COLLABORATION SOLUTIONS OF MICROSOFT 365 * Describe the collaboration capabilities and benefits of Microsoft 365 * Describe how Microsoft Teams promotes collaboration and enhances teamwork * Describe the Microsoft Viva apps * Describe how Yammer helps communities connect and grow 7 - DESCRIBE ENDPOINT MODERNIZATION, MANAGEMENT CONCEPTS, AND DEPLOYMENT OPTIONS IN MICROSOFT 365 * Describe the endpoint management capabilities of Microsoft 365 * Compare the differences of Windows 365 and Azure Virtual Desktop * Describe the deployment and release models for Windows-as-a-Service (WaaS) * Identify deployment methods and update channels for Microsoft 365 Apps 8 - DESCRIBE ANALYTICS CAPABILITIES OF MICROSOFT 365 * Describe the capabilities of Viva Insights * Describe the capabilities of the Microsoft 365 admin center and Microsoft 365 user portal * Describe the reports available in the Microsoft 365 admin center and other admin centers 9 - DESCRIBE THE SERVICES AND IDENTITY TYPES OF AZURE AD * Describe Azure Active Directory * Describe the available Azure AD editions * Describe Azure AD identity types * Describe the types of external identities * Describe the concept of hybrid identity 10 - DESCRIBE THE ACCESS MANAGEMENT CAPABILITIES OF AZURE AD * Describe Conditional Access in Azure AD * Describe the benefits of Azure AD roles and role-based access control 11 - DESCRIBE THREAT PROTECTION WITH MICROSOFT 365 DEFENDER * Describe Microsoft 365 Defender services * Describe Microsoft Defender for Office 365 * Describe Microsoft Defender for Endpoint * Describe Microsoft Defender for Cloud Apps * Describe Microsoft Defender for Identity * Describe the Microsoft 365 Defender portal 12 - DESCRIBE SECURITY CAPABILITIES OF MICROSOFT SENTINEL * Describe how Microsoft Sentinel provides integrated threat management * Understand Sentinel costs 13 - DESCRIBE THE COMPLIANCE MANAGEMENT CAPABILITIES IN MICROSOFT PURVIEW * Describe the Microsoft Purview compliance portal * Describe Compliance Manager * Describe use and benefits of compliance score 14 - DESCRIBE THE SERVICE TRUST PORTAL AND PRIVACY AT MICROSOFT * Describe the Service Trust Portal * Describe Microsoft's privacy principles * Describe Microsoft Priva 15 - DESCRIBE MICROSOFT 365 PRICING, LICENSING, AND BILLING OPTIONS * Explore pricing models for Microsoft cloud services * Explore the billing and bill management options * Explore the available licensing and management options 16 - DESCRIBE SUPPORT OFFERINGS FOR MICROSOFT 365 SERVICES * Explore support options for Microsoft 365 services * Explain service level agreement (SLAs) concepts * Identify how to track the service health status * Explore how organizations can share feedback on Microsoft 365 services

Duration 2 Days 12 CPD hours This course is intended for This course can be valuable for anyone who needs to write basic SQL or Transact-SQL queries. This includes anyone working with data as a data analyst, a data engineer, a data scientist, a database administrator or a database developer. It can also be useful for others peripherally involved with data, or wanting to learn more about working with data such as solution architects, students and technology managers. This course will teach the basics of Microsoft's dialect of the standard SQL language: Transact-SQL. Topics include both querying and modifying data in relational databases that are hosted in Microsoft SQL Server-based database systems, including: Microsoft SQL Server, Azure SQL Database and, Azure Synapse Analytics. 1 - INTRODUCTION TO TRANSACT-SQL * Work with schemas * Explore the structure of SQL statements * Examine the SELECT statement * Work with data types * Handle NULLs 2 - SORT AND FILTER RESULTS IN T-SQL * Sort your results * Limit the sorted results * Page results * Remove duplicates * Filter data with predicates 3 - COMBINE MULTIPLE TABLES WITH JOINS IN T-SQL * Understand joins concepts and syntax * Use inner joins * Use outer joins * Use cross joins * Use self joins 4 - WRITE SUBQUERIES IN T-SQL * Understand subqueries * Use scalar or multi-valued subqueries * Use self-contained or correlated subqueries 5 - USE BUILT-IN FUNCTIONS AND GROUP BY IN TRANSACT-SQL * Categorize built-in functions * Use scalar functions * Use ranking and rowset functions * Use aggregate functions * Summarize data with GROUP BY * Filter groups with HAVING 6 - MODIFY DATA WITH T-SQL * Insert data * Generate automatic values * Update data * Delete data * Merge data based on multiple tables ADDITIONAL COURSE DETAILS: Nexus Humans DP-080T00 Querying Data with Microsoft Transact-SQL 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 DP-080T00 Querying Data with Microsoft Transact-SQL 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.

Want to learn how to use Maven and SonarQube effectively for code building and code quality analysis as a DevOps engineer? Then you are in the right place. This learner-centered hands-on course will help you gain confidence in using important DevOps tools such as SVN, Maven, Jenkins, Chef, Puppet, Nagios, Splunk, Selenium, and more. Some basic knowledge of Linux, Git, and AWS EC2 will help you get the most out of this course.

A complete course on Sqoop, Flume, and Hive: Ideal for achieving CCA175 and Hortonworks Spark Certification

Duration 5 Days 30 CPD hours This course is intended for This course is intended for professional web developers who use Microsoft Visual Studio in an individual-based or team-based, small-sized to large development environment. Candidates for this course are interested in developing advanced web applications and want to manage the rendered HTML comprehensively. They want to create websites that separate the user interface, data access, and application logic. Overview Describe the Microsoft Web Technologies stack and select an appropriate technology to use to develop any given application. Design the architecture and implementation of a web application that will meet a set of functional requirements, user interface requirements, and address business models. Configure the pipeline of ASP.NET Core web applications using middleware, and leverage dependency injection across applications. Develop a web application that uses the ASP.NET Core routing engine to present friendly URLs and a logical navigation hierarchy to users. Create Views in an application that display and edit data and interact with Models and Controllers. Connect an ASP.NET Core application to a database using Entity Framework Core. Implement a consistent look and feel across an entire web application. Write JavaScript code that runs on the client-side and utilizes the jQuery script library to optimize the responsiveness of an web application. Add client side packages and configure Task Runners. Run unit tests and debugging tools against a web application in Visual Studio 2022. Write an application that authenticates and authorizes users to access content securely using Identity. Build an application that resists malicious attacks. Use caching to accelerate responses to user requests. Use SignalR to enable two-way communication between client and server. Describe what a Web API is and why developers might add a Web API to an application. Describe how to package and deploy an ASP.NET Core web application from a development computer to a web server. In this 5-day course, professional web developers will learn to develop advanced ASP.NET Core applications using .NET tools and technologies. The focus will be on coding activities that enhance the performance and scalability of the Web site application. MODULE 1: EXPLORING ASP.NET CORE * Introducing of Microsoft Web Technologies * Getting Started with Razor Pages in ASP.NET Core * Introducing ASP.NET Core MVC MODULE 2: DESIGNING ASP.NET CORE MVC WEB APPLICATIONS * Planning in the Project Design Phase * Designing Models, Controllers and Views MODULE 3: CONFIGURE MIDDLEWARE AND SERVICES IN ASP.NET CORE * Configuring Middlewares * Configuring Services MODULE 4: DEVELOPING CONTROLLERS * Writing Controllers and Actions * Configuring Routes * Writing Action Filters MODULE 5: DEVELOPING VIEWS * Creating Views with Razor Syntax * Using HTML Helpers and Tag Helpers * Reusing Code in Views MODULE 6: DEVELOPING MODELS * Creating MVC Models * Working with Forms * Validating User Input MODULE 7: USING ENTITY FRAMEWORK CORE IN ASP.NET CORE * Introduction to Entity Framework Core * Working with Entity Framework Core * Use Entity Framework Core to connect to Microsoft SQL Server MODULE 8: USING LAYOUTS, CSS AND JAVASCRIPT IN ASP.NET CORE * Using Layouts * Using CSS and JavaScript * Using JavaScript Libraries MODULE 9: CLIENT-SIDE DEVELOPMENT * Applying Styles and Responsive Design * Using Task Runners * Looking at ASP.NET Core Blazor MODULE 10: TESTING AND TROUBLESHOOTING * Testing ASP.NET Core Applications * Implementing an Exception Handling Strategy * Logging ASP.NET Core Applications MODULE 11: MANAGING SECURITY * Authentication in ASP.NET Core * Authorization in ASP.NET Core * Defending from Common Attack MODULE 12: PERFORMANCE AND COMMUNICATION IMPLEMENTING A CACHING STRATEGY * Managing State * Supporting Two-way Communication MODULE 13: IMPLEMENTING WEB APIS * Introducing Web APIs * Developing a Web API * Calling a Web API MODULE 14: HOSTING AND DEPLOYMENT * Hosting and Deploying On-premises * Deploying to Microsoft Azure * Looking at Microsoft Azure Fundamentals

A carefully structured advanced-level course on Apache Spark 3 to help you clear your job interviews. This course covers advanced topics and concepts that are part of the Databricks Spark certification exam. Boost your skills in Spark 3 architecture and memory management.