84 Ethics courses in Cardiff delivered Live Online

Feeling overwhelmed by multiple tasks? Ready to enhance your product management strategy with AI technology? It’s time to meet your new AI partner! Our course, “Unlocking the Power of AI,” will demonstrate how cutting-edge tools like Generative Pre-trained Transformers (GPTs) can simplify your workflow and bolster your decision-making process. In modern-day fast paced commercial enterprise world, adaptability is vital for success. As a product manager, you oversee the entire product lifecycle—from concept to launch and beyond. With Certified Product Management techniques, you can navigate changing market dynamics, prioritize features efficiently, and deliver value to customers quickly. However, agility alone isn’t sufficient. To excel in your role, embrace the potential of AI. By integrating AI into your practices, you can automate tasks, analyze data effortlessly, and make informed decisions. Picture having a virtual assistant capable of analyzing data and predicting market trends. With AI as your ally, you can focus on engaging customers, innovating, and strategic planning. Don’t hesitate. Embrace the future of product management now. Join us on this journey to unlock the full potential of AI, revolutionizing your workflow and achieving your goals faster than ever before. What You'll Learn (in just 3 hours!) AI 101 for Product Managers We'll break down the buzzwords and get you up to speed on how AI (especially those clever GPTs) can transform your work life. Market Research Master Think of your new AI pal as a super-powered market researcher. Learn how to analyze competitor data, customer feedback, and trends faster than you can say "pivot!" AI-Powered Strategy Say goodbye to gut feelings and hello to data-driven insights. Discover how AI helps you strategize, prioritize features, and build roadmaps that will make your product shine. Hands-on Workshop Dive into real-world scenarios and use GPT tools to tackle market analysis, craft user stories, and nail down your product roadmap. Ethics in the AI Age We'll explore responsible AI use and make sure you understand the potential pitfalls. Because with great power comes great responsibility! Our AI + Your Workflow = Dream Team We'll cover how to access our Product Management tool, how to use it effectively and fit it seamlessly into your existing processes. The future of Product Management is here, don’t get left behind. This course is perfect for Product managers and owners are essential drivers of product success, constantly challenged to balance priorities, navigate complex decisions, and foster innovation in competitive markets. With technology advancing rapidly and consumer preferences evolving, staying ahead can be daunting. Our training programs offer a solution. Designed for product managers and owners, they equip you with the tools, insights, and strategies to enhance productivity, make informed decisions, and ignite innovation. Our courses empower you to navigate modern challenges successfully. Whether you seek to refine strategic planning, optimize product development, or enhance customer engagement, our tailored programs cater to your needs. Join us on a journey to unlock your full potential and propel your career to new heights as a product manager or owner. The Takeaway Empowerment: Leave this workshop feeling empowered, armed with a potent toolkit for achieving product success. AI in Product Management: Recognize that AI is the future of product management, and this course will equip you to leverage its potential effectively. Leadership Position: Position yourself as a leader in product management by embracing AI and staying ahead of industry trends. Innovation: Embrace innovation and drive change within your organization with the insights gained from this course. Confidence: Approach the future with confidence, knowing that you have the skills and knowledge to navigate the evolving landscape of product management.

Duration 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Estate Agent Diploma Course Overview The Estate Agent Diploma is designed for individuals looking to develop a comprehensive understanding of the property industry. This course covers key areas such as property law, valuation techniques, and the process of buying and selling properties. Learners will gain insight into the daily responsibilities of estate agents, including client relations, property marketing, and market analysis. The course offers a valuable foundation for those looking to enter the real estate sector, providing the knowledge required to pursue a career as an estate agent. By the end of the course, learners will be equipped with the essential skills needed to navigate the property market with confidence. Course Description This diploma course offers in-depth coverage of various aspects of estate agency work, including property laws, valuation practices, and the sale and purchase process. Learners will explore topics such as client communication, marketing strategies, and legal obligations, ensuring they have a well-rounded knowledge of the industry. The course materials are structured to provide a clear understanding of market trends, the role of estate agents, and customer service in real estate. Throughout the course, learners will gain the skills necessary to work effectively in the property sector, including key insights into the regulatory environment and professional ethics. Estate Agent Diploma Curriculum Module 01: Introduction to Estate Agency Module 02: Property Law and Regulations Module 03: Understanding Property Valuation Module 04: The Buying and Selling Process Module 05: Marketing and Advertising Properties Module 06: Client Communication and Negotiation Module 07: Managing Property Listings and Viewings Module 08: Professional Ethics and Industry Standards (See full curriculum) Who is this course for? Individuals seeking to pursue a career in estate agency. Professionals aiming to enhance their skills in property sales and management. Beginners with an interest in the property industry. Those looking to understand the legal and regulatory aspects of property transactions. Career Path Estate Agent Property Manager Lettings Agent Real Estate Consultant Property Sales Negotiator

Translation: Freelance Translator Course Overview This course is designed to provide learners with a comprehensive understanding of freelance translation, from foundational concepts to professional practices. Participants will gain valuable insights into the world of freelancing, covering topics such as client acquisition, project management, and professional ethics. By the end of the course, learners will be equipped with the essential knowledge and skills to start and sustain a successful freelance translation career, ensuring they are well-prepared for the challenges of the industry. Course Description In this course, learners will explore the fundamental aspects of freelance translation, including an introduction to the industry, the roles and responsibilities of a freelance translator, and how to navigate the complexities of freelancing. Topics include setting up a home office, using computer-assisted translation (CAT) tools, marketing services, managing client relationships, and ensuring translation quality. Learners will also delve into the financial aspects of freelancing, including setting rates, invoicing, and getting paid for work. By the end of the course, participants will be well-equipped to start their own freelance translation business and build a sustainable career. Translation: Freelance Translator Curriculum Module 01: An Overview of Translation Module 02: Introduction to Freelancing Module 03: Introduction to Freelance Translator Module 04: Activities Before Getting Started Module 05: Finding Clients Module 06: Managing the Work Module 07: Marketing Module 08: CAT Tools in Translation Module 09: Getting Paid for The Work Module 10: Setting Up Home Office Module 11: Professional Ethics of Freelance Translators Module 12: Ensuring Quality (See full curriculum) Who is this course for? Individuals seeking to start a career in freelance translation. Professionals aiming to transition into freelancing or broaden their skillset. Beginners with an interest in translation and the freelancing industry. Anyone interested in developing the skills to work independently as a translator. Career Path Freelance Translator Translation Project Manager Language Specialist for Agencies Freelance Proofreader/Editor Content Localisation Expert

News Writing, Production and Reporting Course Overview This course on News Writing, Production and Reporting offers a comprehensive introduction to the core elements of newspaper journalism. Learners will explore essential techniques in news writing, interviewing, reporting, and production, equipping them with the skills needed to craft clear, accurate, and engaging news stories. The programme emphasises the ethical and legal responsibilities of journalists, alongside developing strong writing and reporting skills tailored to contemporary media environments. By the end of the course, participants will understand the principles of newspaper journalism and gain confidence in producing professional news content suitable for a variety of platforms, ensuring readiness for roles in the fast-paced journalism sector. Course Description Delving deeper into the craft of newspaper journalism, this course covers the historical context, development, and evolving nature of the industry. Learners will study interview techniques, news writing formats, production workflows, and specialised reporting areas such as court reporting and niche journalism. Legal frameworks and journalistic ethics form a critical part of the curriculum, ensuring an informed and responsible approach to reporting. Additional topics include feature story writing and health and safety considerations for journalists. Through a structured learning experience, students will develop analytical, communication, and editorial skills vital for effective storytelling in print and digital media, preparing them for a dynamic and rewarding career in journalism. News Writing, Production and Reporting Curriculum Module 01: Introduction and Principles of Newspaper Journalism Module 02: History and Development of Newspaper Journalism Module 03: Interviewing for Newspaper Journalism Module 04: News Writing Module 05: News Production Module 06: News Reporting Module 07: Writing Skills for Newspaper Journalists Module 08: Newspaper Journalism Law Module 09: Court Reporting Module 10: Journalism Ethics Module 11: Niche Journalism Module 12: Tips on Writing a Good Feature Story Module 13: Health and Safety for Journalists (See full curriculum) Who is this course for? Individuals seeking to build foundational skills in newspaper journalism. Professionals aiming to advance their career in media and communications. Beginners with an interest in news writing, reporting, and media production. Anyone wishing to understand the legal and ethical aspects of journalism. Career Path Newspaper Reporter News Editor Broadcast Journalist Feature Writer Court Reporter Media Communications Specialist Digital Content Producer

Fashion Law Course Overview This Fashion Law course offers a comprehensive exploration of the legal principles and frameworks shaping the fashion industry. Learners will gain insight into essential areas such as intellectual property rights, brand protection, retail regulations, counterfeiting, and ethical practices including sustainability. The course equips individuals with the knowledge to navigate complex legal challenges faced by fashion businesses, designers, and retailers. By the end, learners will understand how fashion law intersects with business law and how it protects creativity and commerce in a dynamic global market. This course is valuable for anyone interested in the legal aspects influencing fashion, helping them to make informed decisions, safeguard brand identity, and foster ethical practices within the industry. Course Description This course delves into the key legal topics relevant to the fashion sector, starting with an introduction to fashion law and its role within broader business law contexts. It covers retailing regulations, detailed analysis of intellectual property rights with a two-part focus on brand protection, and the impact of counterfeiting on the industry. Brand licensing is also examined as a strategic business tool. Additionally, the course addresses contemporary issues such as ethics, sustainability, and the rise of green fashion, reflecting the industry's growing environmental concerns. Learners will develop a thorough understanding of legal frameworks and gain skills to assess legal risks, protect intellectual property, and contribute to responsible fashion business practices. Fashion Law Curriculum Module 01: Introduction to Fashion Law Module 02: Fashion Law as Business Law Module 03: Retailing Module 04: Intellectual Property Rights: Brand Protection Part-I Module 05: Intellectual Property Rights: Brand Protection Part-II Module 06: Counterfeiting Module 07: Brand Licensing Module 08: Ethics, Sustainability and Green Fashion (See full curriculum) Who is this course for? Individuals seeking to understand legal issues in the fashion industry. Professionals aiming to enhance their knowledge of fashion business law. Beginners with an interest in fashion, law, and intellectual property. Entrepreneurs and brand managers in the fashion sector. Career Path Fashion Legal Consultant Brand Protection Specialist Intellectual Property Advisor for Fashion Businesses Retail Compliance Officer Ethical Fashion Coordinator Brand Licensing Manager

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.

Birth Doula Course Overview This Birth Doula course is designed to provide learners with comprehensive knowledge and skills to support expectant mothers throughout pregnancy, childbirth, and the postpartum period. Participants will gain a solid understanding of antenatal, labour, and postnatal care, along with key aspects of emotional support for both mothers and families. The course prepares learners to support women in their journey through pregnancy, offering valuable insight into maternal health, newborn care, and mental wellbeing. Upon completion, learners will be equipped to offer invaluable assistance to women during this critical time, ensuring a supportive and compassionate birth experience. Course Description The Birth Doula course covers essential aspects of maternity care, including a detailed understanding of pregnancy, childbirth, and the postpartum period. Learners will explore various topics such as antenatal care, the clinical examination of pregnant women, and management of common pregnancy symptoms. They will also learn about the care of women during labour, including postpartum support and infant care. Mental health considerations for mothers, grief, bereavement, and family planning are all crucial aspects addressed in this course. Learners will gain knowledge of effective communication, empathy, and ethics, which are essential when supporting women through this journey. By completing this course, learners will acquire skills to become a trusted companion for women during one of the most important times in their lives. Birth Doula Curriculum Module 01: Introduction to Birth Doula Module 02: A Woman’s Body in Pregnancy Module 03: Antenatal Care during Pregnancy Module 04: Management of Common Symptoms of Pregnancy Module 05: Clinical Examination of Pregnant Women Module 06: Care of a Woman during Labour Module 07: Postpartum Care Module 08: Screening Newborn Baby Module 09: Infant Care Module 10: Mental Health of the Mother Module 11: Grief and Bereavement Module 12: Contraception and Family Planning Module 13: Effective Communication Module 14: Empathy and Comfort Skills Module 15: Ethics in Doula (See full curriculum) Who is this course for? Individuals seeking to support pregnant women and families. Professionals aiming to enhance their maternity care practice. Beginners with an interest in childbirth and women's health. Aspiring doulas wishing to enter the field of maternal care. Those interested in developing expertise in supporting emotional wellbeing during pregnancy. Career Path Birth Doula Maternity Support Worker Labour and Delivery Assistant Postpartum Care Specialist Women's Health Educator Family Support Worker

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Workplace Mediation