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PYTHON BOOTCAMP: This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts . You will be fully fluent and confident as a Python data analyst, with full understanding of Python Programming. From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards The course is a practical, instructor-lead program.

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.

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds

LOOKING FOR: YA/NA FANTASY, SFF, HORROR, ADULT FICTION John Baker (he/him) joined the Bell Lomax Moreton agency in 2019, cultivating a list shaped around his passion for science fiction, fantasy, and horror, though has lately also branched out into action/adventure fiction. John focuses on authors writing in the Adult, New Adult, and YA spaces. John leads the wider agency's film & TV desk, is the Secretary of the Association of Author’s Agents, and the co-chair of the AAA’s Bridge Committee. He also serves on the Kingston University MA Publishing Advisory Board. Under the umbrella of speculative fiction, John is looking for fantasy, science fiction, horror, romantasy, or literary speculative fiction. He has built a reputation as a champion of underrepresented voices and stories, be it from creators hailing from the global majority and their diasporas or neurodiverse authors, and naturally gravitates towards this kind of storytelling. In short, if he’s never read a story like yours before, he wants to see it. Adult fantasy: John loves beefy epic fantasy, especially non-Anglo Christian-inspired. Give him an immersive world, a fresh magical or mythic system, and an exciting cast of characters and he’ll be happy. He is a broad church in the genre so loves a political fantasy, swords and sorcery, courtly intrigue, monster hunting and dastardly villains. John is keen to find an urban fantasy that feels fresh and fun and he’s a sucker for a heroic quest narrative. He’s also very open to fantasy that isn’t easily categorised, but it is playing in that world. John is keenly hunting for more historical fantasy, especially inspired by modern history. He’s had fun with mythological retellings in the past, but as ever, let’s make sure it’s shining the spotlight on new stories. He would also love fantasy that centres on types of relationships less celebrated in fantasy, such as established and secure married couples, or siblings. NA/YA fantasy: In this genre, most importantly, John wants to have a good time, whether it’s swoon-worthy kisses in lush ball gowns, or gruesome gore and monsters, so send him pacy, plot-filled adventures. He’d love more books that teenage boys would love: Skullduggery Pleasant forever! Romantasy: The thriving new romantasy genre comes with its own set of challenges, so John wants to know what makes your romantasy different; what will set it out from the (very crowded!) market. Give it completely barmy stakes, cool and unique new settings, or a love story that will make your jaw drop. To be clear, he’s happily sorted for a human person meets a fae creature in the spooky woods. Also, cosmic romance is the genre of the future. Give him romantasy in space. Easy. Horror: John and horror are old friends. He loves horror inspired by myth and folklore, subversive weird horror that leaves your eyebrows in your hairline, historical horror that pulls from ghastly true stories, and anything that you’ll be reading with the light on. He also loves a gothic element and is particularly looking for horror with a strong romantic throughline, fun YA horror, and female & NB horror authors. Science fiction: SF is coming back! And John has been shouting about that. He loves to see an adventurous found-family romp through space or an epic, crunchy space opera. Speculative near-future is fun too, in the vein of Black Mirror’s more uplifting episodes, (e.g. San Junipero). He loves YA science fiction as well; the more creative the better. Literary: John is open to finding more rich magical realism or something character-led yet supernatural and would love a high-concept mystery, in the vein of Stuart Turton. He also loves spec fic that uses the speculative lightly as a way of confronting a deeper truth in society today. Weird stuff: John wants books that will blow people’s minds and defy categorisation. This is hard to describe, but think Gideon The Ninth, The Library At Mount Char, This Is How You Lose The Time War. John loves a pitch that leaves the editors baffled but intrigued. Action/Adventure, Historical Adventure, Espionage: John is branching out into non-speculative adventures, such as John Le Carré, Lee Child, Ian Flemming, and Mick Herron. More as his taste develops, but the hunt is on! Not looking for: military sci-fi or hard SF, or anything with biblical “character wakes up in purgatory/heaven/hell” narratives. The right comedic fantasy has yet to hit his inbox, but please don’t comp Douglas Adams or Sir Terry. John would like you to submit a covering letter, 1-2 page synopsis and the first three chapters (or 5,000 words whichever is longest) of your manuscript in a single word document. (In addition to the paid sessions, John is kindly offering one free session for low income/under-represented writers. Please email agent121@iaminprint.co.uk to apply, outlining your case for this option which is offered at the discretion of I Am In Print).  By booking you understand you need to conduct an internet connection test with I Am In Print prior to the event. You also agree to email your material in one document to reach I Am In Print by the stated submission deadline and note that I Am In Print take no responsibility for the advice received during your agent meeting. The submission deadline is: Monday 12th May 2025

Master DeepSeek AI with this CPD-accredited course! Learn automation, coding, and business solutions to boost productivity and career growth.

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online. Learn to code a Password Validator in 1 hour. 

Understand and mitigate your own personal drivers of conflict

Persuade your audience through storytelling

Duration 5 Days 30 CPD hours This course is intended for This course is intended for novice database developers, database administrators, Business Intelligence developers, report creators, and application developers who have an understanding of relational database concepts and have basic Windows navigation skills. Overview Create single table SELECT queries Create multiple table SELECT queries Filter and sort data Insert, update, and delete data Query data using built-in functions Create queries that aggregate data Create subqueries Create queries that use table expressions Use UNION, INTERSECT, and EXCEPT on multiple sets of data Implement window functions in queries Use PIVOT and GROUPING SETS in queries Use stored procedures in queries Add error handling to queries Use transactions in queries This five-day instructor-led course is intended for IT professionals who wish to use the Transact-SQL language to query and configure Microsoft SQL Server. Students are typically database developers and database administrators, but might also be Business Intelligence developers, report creators, or application developers. In this course, students learn how to query single tables, join data from multiple tables, filter and sort data, modify data, use procedures and functions, and implement error handling. Prerequisites Basic understanding of relational databases. Basic Windows knowledge. Module 1: Introduction to Transact-SQL What is Transact-SQL The SELECT statement The WHERE clause Sorting results Calculations CASE expressions Module 2: Joining tables with Transact-SQL The JOIN clause Inner joins Outer joins Self joins and cross joins Module 3: Filtering and sorting results Implement the ORDER BY clause Filter data with the WHERE clause Limit the number of rows returned by a query Implement NULL logic Module 4: SQL Server data types Understand data types Implement string data types Implement temporal data types Module 5: Inserting, updating and deleting data Insert new records Update existing records Delete data Module 6: Using SQL Server functions with Transact-SQL Understand function types in SQL Server Convert data using functions Implement logical functions Work with NULL data using functions Module 7: Aggregating data with Transact-SQL Implement aggregation in SQL Server Group records in SQL Server Filter aggregated data Module 8: Implement subqueries with Transact-SQL Implement scalar and multi-valued sub-queries Implement correlated subqueries Implement existence checks with subqueries Module 9: Create queries that use table expressions Create views Create table-valued functions Implement derived tables Implement common table expressions Module 10: Use UNION, INTERSECT, EXCEPT and APPLY on multiple sets of data Write queries with the UNION operator Write queries with the INTERSECT and EXCEPT operators Write queries with the APPLY operator Module 11: Implement window functions in queries Understand window functions Impement window functions Module 12: Use PIVOT and grouping sets in queries Implement PIVOT in queries Implement grouping sets in queries Module 13: Use stored procedures in queries Query data with stored procedures Interact with stored procedures using input and output parameters Write simple stored procedures Pass dynamic SQL to SQL Server Module 14: Implement programming features in Transact-SQL Understand T-SQL programming elements Implement loops and conditions in T-SQL queries Module 15: Add error handling to queries Understand SQL Server error handling Implemet structured exception handling Module 16: Use transactions in queries Understand database transactions Implement transactions in T-SQL

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