15160 AI courses

Duration 1 Days 6 CPD hours For the better part of every day, we are communicating to and with others. Whether it?s the speech you deliver in the boardroom, the level of attention you give your spouse when they are talking to you, or the look you give the cat, it all means something. This workshop will help participants understand the different methods of communication and how to make the most of each of them. 1 - Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives 2 - The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication 3 - Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place 4 - Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed 5 - Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures 6 - Speaking Like a STAR S = Situation T = Task A = Action R = Result Summary 7 - Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others 8 - Asking Good Questions Open Questions Closed Questions Probing Questions 9 - Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies 10 - Mastering the Art of Conversation Level One: Discussing General Topics Level Two: Sharing Ideas and Perspectives Level Three: Sharing Personal Experiences Our Top Networking Tips 11 - Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages 12 - Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Additional course details: Nexus Humans Communication Strategies 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 Communication Strategies 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.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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.

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Why Choose Unity 3D Game Design Training Course? Course Link Unity transforms ideas into reality, offering limitless possibilities for 2D and 3D games, VR, AR, and AI experiences. From films to architecture, training videos, and interactive tutorials, Unity revolutionizes industries with its interactive engagement, making it the top choice for solutions. Duration: 10 hrs Method: 1-on-1, Personalized attention Schedule: Tailor your own hours of your choice, available from Mon to Sat between 9 am and 7 pm Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. Coding in Unity? Coding is optional in Unity, thanks to the visual scripting tool, Bolt. Users can implement ideas without coding using flow graphs and state graphs for low-level and high-level logic. Paid tools like PlayMaker and Adventure Creator offer more advanced gameplay and AI behaviors. How Does Unity's Game Engine Work? Unity operates as a versatile scene player, initializing settings for graphics, audio, and input devices at game start. It loads scenes with assets and game objects, executing a cycle that renders scenes, runs physics simulations, and handles events, providing a seamless and dynamic game experience. Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. 10-hour Unity 3D Game Design Training Course: Module 1: Introduction to Unity 3D (2 hours) - What is Unity 3D and why use it for game design? - Understanding the Unity 3D interface - Creating and managing projects in Unity 3D - Importing and managing assets in Unity 3D - Understanding game objects and components in Unity 3D Module 2: Game Mechanics (2 hours) - Basic game mechanics and concepts - Player movement and camera control - Creating and controlling game objects - Working with physics and collision detection - Creating interactive environments Module 3: Scripting with C# (2 hours) - Introduction to C# scripting language - Understanding variables and data types in C# - Creating and using functions in C# - Controlling game objects with C# - Understanding game loops and events Module 4: User Interfaces and Audio (2 hours) - Designing user interfaces in Unity 3D - Creating and using buttons, sliders, and input fields - Audio import and editing in Unity 3D - Creating and controlling game sound effects and background music Module 5: Optimization and Deployment (2 hours) - Understanding game optimization in Unity 3D - Optimizing game performance with scripting - Building and testing games for desktop and mobile platforms - Publishing games on the web or app stores Introduction to Unity: - Introduction to gaming and the game development process - Unity Basics - Interface - Inspector - Project and Hierarchy Starting Making a Game: - Working with Projects - Creating Projects - Importing Geometry - Importing Textures - Using the terrain generator to make the terrain - Creating basic primitives in Unity Materials: - Working with materials 1 - Working with materials 2 - Finishing materials on all objects Lighting: - Creating lights - Adjusting Lights - Creating Sunlight Animation: - Animating objects - Animating lights - Adjusting Animations Audio: - Adding Sound - Interacting with sound - Modifying sound Programming Tools: - JavaScript - Editor for JavaScript - Variables and functions - Simple programming Testing: - Testing the game - Fixing bugs - Making changes in games Building the Game: - Game authoring Settings - Building the game for windows - Playing the game Utilize Unity Pro, the ultimate real-time development platform, to craft 3D, 2D, VR, and AR experiences across diverse industries. From games to auto, AEC, and film, Unity Pro empowers you to create immersive content with multi-platform support. Visit https://www.unity.com/ to kickstart your journey today, enabling faster iterations and business growth through unparalleled development capabilities.

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

Explore the various concepts and innovative technologies that convert the traditional banking system to digital banking system. Enrol the Digital Banking for Beginners course and learn more about the digitalization process. The course presents the latest news about world banking by illustrating the example from nine countries. You will understand the difference between traditional banking and new generation banking. The course also explains the reasons behind the transformation of traditional banking to digital banking. The necessity of embracing the digital banking system will be discussed in the course. The concepts and new innovations in banking, and the examples of web-based platforms such as the Proliferation of Internet Banking, Mobile Banking and 'Direct Banking' concept will also be thoroughly explained in the course. Additionally, the course teaches about innovative technologies such as artificial intelligence, Internet of Things (IOT), Machine Learning, Block-chain, Big Data and more. By the end of the course, you will learn the essential front-end and back-end projects that make an organization digital. What Will I Learn? It just takes 60 minutes or less of your time, to transform you in absorbing the new generation banking knowledge at a base level. As this is shared by a banking Industry veteran, it covers entire banking digital life-journey from front-end to back-end till 2018. Therefore it should generate enough confidence in you, of becoming aware of actual happenings in digital banking world. However, it is important to know that this knowledge is at a base level. But its a great start for your life, as you shall start speaking more confidently on banking innovations and digital banking than ever before . This course helps participant to seek awareness level understanding of Digital Banking in contemporary era both from fancy innovative names and also projects close to CIO's heart such as Back-end Modernization. This course gives practical view of what projects are done in front end as well as Back end to make organization digital. Requirements There is no specific banking knowledge needed to attend this course. Who is the target audience? Any Aspiring interview candidate who is looking for a new job in banking sector, Any undergraduate, graduate or post-graduate student, any employee of a bank, employee in IT companies working BFS sector, anyone working on banking transaction for his organization or simply people who are interested to learn digital banking. Any school students who would like to take projects or have interest in studying new-generation Banking can also take this course too. Story of Digital Banking -- An overview section Introduction FREE 00:02:00 Moving from Traditional Banking to New-gen Banking Moving from Traditional Banking to New-gen Banking 00:08:00 Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept 00:07:00 Use of Social media in Banking and arrival of Fintech Firms Use of Social media in Banking and arrival of Fintech Firms 00:09:00 Innovative technologies IOT, AI, ML, Block-chain,, Big data etc Innovative technologies IOT, AI, ML, Blockchain,, Big data etc 00:10:00 Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank 00:11:00 Course Certification

This comprehensive course will guide you to use the power of Python to evaluate recommender system datasets based on user ratings, user choices, music genres, categories of movies, and their years of release with a practical approach to build content-based and collaborative filtering techniques for recommender systems with hands-on experience.

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

Depending on the risks to your employees you may need a qualified 'first aider(s)' This 3 day course (previously 4 day), which after completion and a satisfactory assessment, permits the holder of the certificate to act as a first aider in the workplace under HSE (First Aid) regulations 1981. The certificate is valid for 3 years.

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.