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A 10 week SATs Success course for students in year 6. Tutoring in English and Tutoring in Maths in a small group year 6 tutor session.

Training duration: 10 hrs. Click here for more info Method: 1-2-1, Personalized attention, Tailored content, Flexible pace, Individual support. Schedule: Personalized training experience with our flexible 1-2-1 sessions. Tailor your own schedule by pre-booking a convenient hour of your choice, available from Monday to Saturday between 9 am and 7 pm. Discover the world of 3D computer graphics and animation with our Autodesk Maya Basic to Fundamentals Training Course. Whether you're a beginner or aspiring artist, this comprehensive program equips you with essential skills in modeling, animation, and rendering. Benefit from interactive learning, experienced instructors, and the option to choose in-person or live online sessions. Enroll now to gain industry-standard knowledge and unleash your creativity in the field of animation and visual effects. Maya Basic to Intermediate Course Course Duration: 10 hours Course Outline: I. Introduction to Maya (1 hour) - Gain an insightful overview of Maya and its diverse applications - Familiarize yourself with the Maya interface and essential tools - Master navigation and viewport controls with ease - Learn the art of creating and managing projects proficiently II. Creating 3D Models (2 hours) - Lay a strong foundation in polygon modeling basics - Craft and shape basic objects and shapes adeptly - Refine and modify objects with precision and creativity - Unlock the art of constructing complex objects using extrusions and bevels III. Texturing and Materials (1 hour) - Venture into the realm of texturing and its significance - Create and skillfully apply materials to enhance visual appeal - Master the art of texture mapping and UV unwrapping techniques - Seamlessly import and incorporate textures and images into your projects IV. Lighting and Rendering (1.5 hours) - Illuminate your creations with fundamental lighting techniques - Set up cameras and compose visually captivating scenes - Master the art of rendering still images and dynamic animations - Explore diverse output options and file formats for professional results V. Animation (2.5 hours) - Embark on an enthralling journey into the world of animation - Effectively utilize keyframe animation and animation curves - Create and edit animation clips for seamless and captivating motion - Dive into the intricacies of rigging and animating a simple character VI. Special Effects (1 hour) - Unleash the potential of particle systems and dynamics - Create and manipulate mesmerizing fluid and fire effects - Craft and refine awe-inspiring special effects such as explosions and smoke VII. Intermediate Modeling Techniques (1 hour) - Elevate your skills with NURBS modeling essentials - Create and modify curves and surfaces with finesse - Dive into the world of crafting organic shapes using NURBS techniques - Employ sculpting tools to create high-resolution and detailed models VIII. Conclusion and Next Steps (0.5 hours) - Recap the wealth of knowledge from the course content - Discover valuable tips and resources for further learning and growth - Engage in a dynamic Q&A session and provide valuable feedback

Aspiring author? We know how frustrating it can be to have a brilliant story idea but feel stuck on where to start. The blank page can be intimidating, and finding the time and confidence to write can seem impossible. This Two-Day Creative Writing Workshop is designed specifically for beginners like you, ready to turn your novel dreams into reality! 🚀✍️

Learn how to code with Python. Work on a small real-life project from conception to tested app, in a team or on your own.

Tea 'N Chat free event - Talk with Textile Artist Nicky Simpson

The WSET Level 2 Award in Wines has full accreditation from OfQual as a Level 2 Vocational Qualification. Through a combination of tasting and theory you will explore the factors that impact the style and quality of wine and learn how to describe wines with confidence. Course Schedule: The 8 x 2-hour online sessions on -  What the course covers Wine tasting: You will learn how to taste and describe wines using the WSET Systematic Approach to Tasting (SAT) Food and wine pairing: You will learn the principles of food and wine pairing Wine service and storage: You will learn the correct way to store and serve wine and how to recognise common faults found in wine Labelling: You will learn how to decode and understand wine labels Factors influencing the style of wine: You will explore how environmental factors, grape-growing, vineyard and maturation options influence the style and quality of the wines made all over the world Grape varieties: You'll learn about the styles of wines produced by the key international red and white grape varieties (Chardonnay, Pinot Grigio, Sauvignon Blanc, Riesling, Cabernet Sauvignon, Pinot Noir, Merlot and Syrah/Shiraz) as well as the styles of wines made with 22 regionally important grape varieties grown in 70 wine regions (GI's) around the world Sparkling and Fortified wines: You will be taught how grape varieties and winemaking processes influence the style of wines in these two key wine categories. No prior wine knowledge is required however the course builds upon the WSET Level 1 Award in Wines course. It is not essential to complete Level 1 to join the Level 2 course but if you are a complete begineer you may wish to consider this option. We recommend you read the course specification document HERE for full details of the content, structure and assesment criteria. Any questions please get in touch. Course delivery The Level 2 Award in Wines online course covers the same syllabus as the classroom course and is delivered in LIVE interactive online lessons by one of our certified wine educators This course includes 16 hours online tuition in 8 x 2hr sessions and we recommend a minimum of 12 hours additional study Your tutor will give you a guided tasting of 12 wines on this course (for details of how to order the wines see below) You will receive access to practice multiple-choice revision questions specific to this course - FREE OF CHARGE Please note a reliable broadband connection is essential for the completion of this online course as are basic computer skills. Examination To obtain the WSET Level 2 Award in Wines Qualification, you will need to successfully pass the exam. The exam is made up of 50 multiple-choice questions to be completed in 1 hour. A mark of 55% is required to pass the exam. The exam is taken online via a Remote Invigilation service giving you the flexibility to take the exam at a time and date of your choice. More details will be sent upon registration. Please ensure you read the information HERE if you wish to take the exam online.  Whats included All WSET course materials posted to you at no extra charge including: Looking Behind the Label course manual, Study Guide, specification and SAT Tasting Card LIVE virtual interactive sessions taught by a Local Wine School WSET Certified Tutor Exclusive access to practice multiple choice questions provided FREE OF CHARGE WSET exam fee Remote Invigilation service Internationally recognised WSET qualification, certificate and pin for those who pass the exam VAT at 20% (VAT receipt can be provided on request) Course Wines It is recommended that at least 12 wines are tasted as part of this course, although this is optional and the cost of wines is not included in the course fee above. Our wine experts have specially selected wines for this course designed to demonstrate specific learning outcomes. We have negotiated a discounted price only available to our online students. Details of how to order your case of wines will be provided when you book your place. The cost is approx £150 including VAT and delivery.  Wine preservation advice is give so that after each tasting exercise you can reseal and return to the wines over the coming days. Special Educational Needs Please make the school aware if you have a condition which may mean that you will qualify for additional help during the exam such as dyslexia. Important dates Registration deadline: please book at least 5 days before the start of the course, to allow time to send materials and order the tasting wines.

The course is a four hour refresher session for those who have completed the Mental Health First Aid two or one day course. Just like physical first aid, we recommend you refresh your skills regularly and keep up-to-date. The four-hour MHFA Refresher course will support MHFAiders® by:  Renewing their skills Updating their knowledge of mental health supports Giving them the chance to practice applying the Mental Health First Aid action plan Providing them access to three years of MHFAider® support and benefits Please note the MHFA Refresher is only for people who have previously complete the MHFA course.Format This is a half day course delivered online Learning takes place through a mix of presentations, group discussions and workshop activities We limit numbers to 25 people per course so that the instructor can keep people safe and supported while they learn What are the MHFAider support & benefits? With access to MHFAider® support and benefits, training doesn't stop when the course comes to an end. We provide continuous support for MHFAiders® – well beyond initial certification – so they are confident, empowered and motivated to carry out their role.  MHFAiders® get automatic 24/7 digital support through the MHFAider Support App®. From there they will find exclusive resources, ongoing learning opportunities and the benefit of joining England’s largest community of trained MHFAiders®.  Access includes:  A resource library of toolkits, guidance, animations and core mental health concepts to support them in their role as an MHFAider® A signposting database through Hub of Hope to find local and national mental health services for additional support Secure conversation journalling to make reflective notes while protecting confidentiality Reminders for wellbeing check ins with the people MHFAiders® are supporting 24/7 text support services through Shout for advice and reassurance on a mental health conversation or to support wellbeing after a difficult conversation Exclusive quarterly webinars to embed and broaden mental health knowledge The benefit of joining England’s largest community of trained MHFAiders®

How can I use reflection to improve my practice

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

This beginner to intermediate level qualification course provides a structured exploration of the world of wine and is suitable for both wine industry professionals and wine enthusiasts. Individuals on this course will gain knowledge of the principal and regionally important grape varieties of the world and the styles of wine they produce. Through a combination of tasting and theory, candidates will explore the factors that impact style and quality and learn how to describe wines with confidence.