1088 Scientist courses

PYTHON BASICS: COURSE DESCRIPTION Excellent for beginners, practical, in small groups of max 4 people, 1 Day Online Instructor-led. You could contact us for your prefereed date. Session 1: Python Data Types and Variables: * Primitive types; Characters & Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python. * Operators and Expressions: * Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.. * Exercise: Calculate Movie Tickets for a Party, Are there enough seats in the cinema? Decision Making & Loops * If statement; If - else statement; If- elif - else statement; Nested if - else; * Exercise: Calculate the travel fee to deliver goods * The while, For loop * Jump statements: break, continue; * Nesting loops. * Exercise: Enter a password, if incorrect 3 times, you are blocked. Session 2: Data Structures * Lists. * Tuples. * Exercise: Hangman Game * Exercise: Get a word for the game from a Json File, store the high score in a Dictionary file Session 3: Files and exceptions * Exception Handling, Exception types; Using try and Except. * Files, streams: Open, Traverse, Read and Create Files: Csv, txt and Json Files. * API: Connecting to API’s. Session 4: OOP * Creating and using custom Functions. * Using parameters and return values. * Creating a Class; Creating an Object; Using an Object; Adding Instance variables; * Class Constructors; Parameterized Constructors. * Inheritance. Override. Session 5: Pandas Dataframe Basics * Getting data into a dataframe: Dict to Dataframe, Dataframe to Dict. Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. * Getting information about the dataframe, * Filter, sort and query a Dataframes, Slicing Dataframes, * Duplicate values,Working with null-values, Sampling. * Exercise: Query the top 1000 grossing movies of the last century Session 6: Built in Functions: String, Math, Random * Python built-in functions: * Strings functions. Maths functions. Random Functions. * Exercise: Find information in prose, to get the sentiment of the prose. * Exercise: Get a word for the game from a txt File * Exercise: Win the lottery INCLUDED: * PCWorkshops's Python Programming Basics Certification * Course notes, exercises and code examples * Revision session after the course -------------------------------------------------------------------------------- REFUND POLICY No Refunds

This FREE in-person event is structured to introduce SMEs to a variety of AI tools that are useful for improving business processes.

Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding. -------------------------------------------------------------------------------- Python Beginners Evenings Course COURSE SUMMARY This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time. It is a Python beginners course and teaches Python coding from scratch to intermediate. Hands-on, practical. We code some real life examples in this course. Duration: 3 Evenings, once per week for 3 weeks 6pm-8pm, of which the first date only shows on the booking. Virtual Classroom: You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket. Who Should Attend? This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive. Course Outline: Session 1: Basics * Python Data Types, Variables, * Operators and Expressions: Arithmetic operators; Relational operators; Assignment operator; Logical operators. * Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else; * Using Loops: The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops. Session 2: Lists. Dictionaries, Json * Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary. Session 3: Built-in functions: * Python Date Functions. Random. Math Functions. String Functions. Python Regex. Session 4: Database: * Connect to a database, create Database, create a table, insert, delete, update records, query a database and display results. Drop database, drop table. Session 5: Files * Exception Handling in Python: Fundamentals of exception handling; Exception types; Using try and except. * Files, streams: Create, Open, Traverse and Read Files: Csv, txt and Json Files. * API: Connecting to API’s Session 6: M ethods, Classes and Objects * Creating and using Function, Working with parameters, Calling functions. * Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s FAQ Do I need Python on my Laptop? Ideally spoken yes, but if not possible, you could use our online platform. Can I pay by BACS? Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Can I pay with PayPal? Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Do I get an invoice? Yes, on request. Can I pay with a PO (Purchase Order Number)? Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Do I get a certificate? Yes, a PCWorkshops Certificate Can I attend in classroom? Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes. Can beginners follow this course? Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered Can I customise the course? Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline. -------------------------------------------------------------------------------- REFUND POLICY No Refunds

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.

Intelligent Yoga Teacher Training (IYTT) is unique amongst teacher training courses. We offer an incisive, thoughtful and intelligent approach to yoga teacher training, driven by the most current scientific developments in anatomy and movement research. Delivered by an elite group of senior yoga teachers at the top of their field, IYTT offers a spacious, immersive modular structure which provides time and space for profound learning, integration and growth. Each of the teaching team draws on decades of practical experience of yoga, including particularly the work of Vanda Scaravelli and somatic, embodied practices.

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

This FREE in-person event is structured to introduce SMEs to a variety of AI tools that are useful for improving business processes.

This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career. -------------------------------------------------------------------------------- PYTHON BOOTCAMP: This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer. If you have more questions goto https://pcworkshopslondon.co.uk/contact.html  [http://pcworkshopslondon.co.uk/contact.html], Or contact us on training@pcworkshopslondon.co.uk [https://pcworkshopslondon.co.uk/] Customise dates, course outline, arrange installments [https://pcworkshopslondon.co.uk/contact.htm] This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession.    Duration: 3 months: * 1 Python class per week, * Plus pratical work, * Plus personal trainer-mentor for 1-1 training, * Plus e-learning materials. Final project : Practical to upload to GitHub and show-case Date and times, choose: * Fridays in London or Online , 10am - 5pm, * or Saturdays in London or Online , 12noon-6pm, * or negotiate your date Study level: Start from beginners level to in-depth, ready to work professionally. Virtual attendance:  online instructor-led  Download: Anaconda.com Pre-requisites: General computer literacy. Oracle Qualification: PCWorkshops Python Programmer Certificate Payments:  You may apply to pay in installments for this Python Training course COURSE OUTLINE Week 1 - 4: Essentials 1. Python Coding Basics 2. Object Oriented programming: Python Object Orientated programming (OOP) 3. UX Principles: UX Principles and applying it on Front-ends with TKinter 4. Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas Week 5 - 10 : All about data 1. Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file 2. Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project 3. Data Analytics: Numpy. Pandas for data analytics and data queries. 4. Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc. 5. Data visualisation: MatPlotLib 6. Prediction: Machine Learning Basics Week 11 and 12: The final touch 1. Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks 2. Python Unit Testing 3. Optional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends INCLUDED: * PCWorkshops Python Course Certificate on completion. * Python Course notes. * Practical Course exercises, Code Examples, Online Materials. * After the course, continuous assistance with practical and preparation for exams * Max group size on this is 4. * Portfolio: Post your Python project online. * Exam preparation and interview questions MORE ABOUT THE ONLINE CLASSROOM *  Attend from your internet connection *  Instructor-led, get instant answers to your questions *  Fully interactive *  Work clearly explained with demonstrations and examples *  Practical exercises to be tried out by delegate WHAT YOU WILL GAIN: * Skills & knowledge: Python coding knowledge and understanding with good practical application   * Certification: Internal PCWorkshops Python certificate * Portfolio: You will have an online portfolio of Python projects  * Experience: Our comprehensive practical makes you job ready -------------------------------------------------------------------------------- REFUND POLICY No Refunds

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - DESIGN A DATA INGESTION STRATEGY FOR MACHINE LEARNING PROJECTS * Identify your data source and format * Choose how to serve data to machine learning workflows * Design a data ingestion solution 2 - DESIGN A MACHINE LEARNING MODEL TRAINING SOLUTION * Identify machine learning tasks * Choose a service to train a machine learning model * Decide between compute options 3 - DESIGN A MODEL DEPLOYMENT SOLUTION * Understand how model will be consumed * Decide on real-time or batch deployment 4 - DESIGN A MACHINE LEARNING OPERATIONS SOLUTION * Explore an MLOps architecture * Design for monitoring * Design for retraining 5 - EXPLORE AZURE MACHINE LEARNING WORKSPACE RESOURCES AND ASSETS * Create an Azure Machine Learning workspace * Identify Azure Machine Learning resources * Identify Azure Machine Learning assets * Train models in the workspace 6 - EXPLORE DEVELOPER TOOLS FOR WORKSPACE INTERACTION * Explore the studio * Explore the Python SDK * Explore the CLI 7 - MAKE DATA AVAILABLE IN AZURE MACHINE LEARNING * Understand URIs * Create a datastore * Create a data asset 8 - WORK WITH COMPUTE TARGETS IN AZURE MACHINE LEARNING * Choose the appropriate compute target * Create and use a compute instance * Create and use a compute cluster 9 - WORK WITH ENVIRONMENTS IN AZURE MACHINE LEARNING * Understand environments * Explore and use curated environments * Create and use custom environments 10 - FIND THE BEST CLASSIFICATION MODEL WITH AUTOMATED MACHINE LEARNING * Preprocess data and configure featurization * Run an Automated Machine Learning experiment * Evaluate and compare models 11 - TRACK MODEL TRAINING IN JUPYTER NOTEBOOKS WITH MLFLOW * Configure MLflow for model tracking in notebooks * Train and track models in notebooks 12 - RUN A TRAINING SCRIPT AS A COMMAND JOB IN AZURE MACHINE LEARNING * Convert a notebook to a script * Run a script as a command job * Use parameters in a command job 13 - TRACK MODEL TRAINING WITH MLFLOW IN JOBS * Track metrics with MLflow * View metrics and evaluate models 14 - PERFORM HYPERPARAMETER TUNING WITH AZURE MACHINE LEARNING * Define a search space * Configure a sampling method * Configure early termination * Use a sweep job for hyperparameter tuning 15 - RUN PIPELINES IN AZURE MACHINE LEARNING * Create components * Create a pipeline * Run a pipeline job 16 - REGISTER AN MLFLOW MODEL IN AZURE MACHINE LEARNING * Log models with MLflow * Understand the MLflow model format * Register an MLflow model 17 - CREATE AND EXPLORE THE RESPONSIBLE AI DASHBOARD FOR A MODEL IN AZURE MACHINE LEARNING * Understand Responsible AI * Create the Responsible AI dashboard * Evaluate the Responsible AI dashboard 18 - DEPLOY A MODEL TO A MANAGED ONLINE ENDPOINT * Explore managed online endpoints * Deploy your MLflow model to a managed online endpoint * Deploy a model to a managed online endpoint * Test managed online endpoints 19 - DEPLOY A MODEL TO A BATCH ENDPOINT * Understand and create batch endpoints * Deploy your MLflow model to a batch endpoint * Deploy a custom model to a batch endpoint * Invoke and troubleshoot batch endpoints

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - PREPARE TO DEVELOP AI SOLUTIONS ON AZURE * Define artificial intelligence * Understand AI-related terms * Understand considerations for AI Engineers * Understand considerations for responsible AI * Understand capabilities of Azure Machine Learning * Understand capabilities of Azure AI Services * Understand capabilities of the Azure Bot Service * Understand capabilities of Azure Cognitive Search 2 - CREATE AND CONSUME AZURE AI SERVICES * Provision an Azure AI services resource * Identify endpoints and keys * Use a REST API * Use an SDK 3 - SECURE AZURE AI SERVICES * Consider authentication * Implement network security 4 - MONITOR AZURE AI SERVICES * Monitor cost * Create alerts * View metrics * Manage diagnostic logging 5 - DEPLOY AZURE AI SERVICES IN CONTAINERS * Understand containers * Use Azure AI services containers 6 - ANALYZE IMAGES * Provision an Azure AI Vision resource * Analyze an image * Generate a smart-cropped thumbnail 7 - CLASSIFY IMAGES * Provision Azure resources for Azure AI Custom Vision * Understand image classification * Train an image classifier 8 - DETECT, ANALYZE, AND RECOGNIZE FACES * Identify options for face detection analysis and identification * Understand considerations for face analysis * Detect faces with the Azure AI Vision service * Understand capabilities of the face service * Compare and match detected faces * Implement facial recognition 9 - READ TEXT IN IMAGES AND DOCUMENTS WITH THE AZURE AI VISION SERVICE * Explore Azure AI Vision options for reading text * Use the Read API 10 - ANALYZE VIDEO * Understand Azure Video Indexer capabilities * Extract custom insights * Use Video Analyzer widgets and APIs 11 - ANALYZE TEXT WITH AZURE AI LANGUAGE * Provision an Azure AI Language resource * Detect language * Extract key phrases * Analyze sentiment * Extract entities * Extract linked entities 12 - BUILD A QUESTION ANSWERING SOLUTION * Understand question answering * Compare question answering to Azure AI Language understanding * Create a knowledge base * Implement multi-turn conversation * Test and publish a knowledge base * Use a knowledge base * Improve question answering performance 13 - BUILD A CONVERSATIONAL LANGUAGE UNDERSTANDING MODEL * Understand prebuilt capabilities of the Azure AI Language service * Understand resources for building a conversational language understanding model * Define intents, utterances, and entities * Use patterns to differentiate similar utterances * Use pre-built entity components * Train, test, publish, and review a conversational language understanding model 14 - CREATE A CUSTOM TEXT CLASSIFICATION SOLUTION * Understand types of classification projects * Understand how to build text classification projects 15 - CREATE A CUSTOM NAMED ENTITY EXTRACTION SOLUTION * Understand custom named entity recognition * Label your data * Train and evaluate your model 16 - TRANSLATE TEXT WITH AZURE AI TRANSLATOR SERVICE * Provision an Azure AI Translator resource * Specify translation options * Define custom translations 17 - CREATE SPEECH-ENABLED APPS WITH AZURE AI SERVICES * Provision an Azure resource for speech * Use the Azure AI Speech to Text API * Use the text to speech API * Configure audio format and voices * Use Speech Synthesis Markup Language 18 - TRANSLATE SPEECH WITH THE AZURE AI SPEECH SERVICE * Provision an Azure resource for speech translation * Translate speech to text * Synthesize translations 19 - CREATE AN AZURE AI SEARCH SOLUTION * Manage capacity * Understand search components * Understand the indexing process * Search an index * Apply filtering and sorting * Enhance the index 20 - CREATE A CUSTOM SKILL FOR AZURE AI SEARCH * Create a custom skill * Add a custom skill to a skillset 21 - CREATE A KNOWLEDGE STORE WITH AZURE AI SEARCH * Define projections * Define a knowledge store 22 - PLAN AN AZURE AI DOCUMENT INTELLIGENCE SOLUTION * Understand AI Document Intelligence * Plan Azure AI Document Intelligence resources * Choose a model type 23 - USE PREBUILT AZURE AI DOCUMENT INTELLIGENCE MODELS * Understand prebuilt models * Use the General Document, Read, and Layout models * Use financial, ID, and tax models 24 - EXTRACT DATA FROM FORMS WITH AZURE DOCUMENT INTELLIGENCE * What is Azure Document Intelligence? * Get started with Azure Document Intelligence * Train custom models * Use Azure Document Intelligence models * Use the Azure Document Intelligence Studio 25 - GET STARTED WITH AZURE OPENAI SERVICE * Access Azure OpenAI Service * Use Azure OpenAI Studio * Explore types of generative AI models * Deploy generative AI models * Use prompts to get completions from models * Test models in Azure OpenAI Studio's playgrounds 26 - BUILD NATURAL LANGUAGE SOLUTIONS WITH AZURE OPENAI SERVICE * Integrate Azure OpenAI into your app * Use Azure OpenAI REST API * Use Azure OpenAI SDK 27 - APPLY PROMPT ENGINEERING WITH AZURE OPENAI SERVICE * Understand prompt engineering * Write more effective prompts * Provide context to improve accuracy 28 - GENERATE CODE WITH AZURE OPENAI SERVICE * Construct code from natural language * Complete code and assist the development process * Fix bugs and improve your code 29 - GENERATE IMAGES WITH AZURE OPENAI SERVICE * What is DALL-E? * Explore DALL-E in Azure OpenAI Studio * Use the Azure OpenAI REST API to consume DALL-E models 30 - USE YOUR OWN DATA WITH AZURE OPENAI SERVICE * Understand how to use your own data * Add your own data source * Chat with your model using your own data 31 - FUNDAMENTALS OF RESPONSIBLE GENERATIVE AI * Plan a responsible generative AI solution * Identify potential harms * Measure potential harms * Mitigate potential harms * Operate a responsible generative AI solution