55815 Courses delivered Online

The Temporary Works Supervisor course will provide you with knowledge of the role. You will also gain a good understanding of risk management on a temporary works site. Course Objectives: By the end of the course, the delegate will gain knowledge of: Have gained an understanding of the importance of cooperation and teamwork on a temporary works site Understand the legal duties of the role Have a stronger awareness of risk management on-site as well as the roles of a supervisor and their fellow employees on site Leave the course with an understanding of the “4C’s”, Communication, Cooperation, Coordination and Competency Course Content: Different groups and types of Temporary Works BS5975:2019 CDM Regulations Legislation and Codes of Practice Temporary Works Register, Design Brief and Design Case studies, policy and procedures, Standard solutions and permitted drawings Risk assessments, method statements Safe systems of work The roles and duties of a Temporary Works Supervisor Assessment: To successfully complete the course, you will need to get 72% or above in the final exam. The trainer encourages the delegates to be interactive and involved throughout the training. Certificate: The certificate for this course is valid for 5 years. Instructions Please note all Temporary Works Supervisor courses with the venue “Remote Learning” will be delivered by a tutor over a video call. This training will be delivered and assessed in English language; therefore, a good standard is required to complete the course. Further attendee information will be sent in a separate email, please check your inbox.

Improve your awareness of mental health and the challenges faced by seafarers, in ISWAN's Maritime Mental Health Awareness training.

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

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

Data Visualization Courses London. In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational visualizations This course is ideal for managers and data analysts who need to make business decisions based on data.

his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects.

Access Introduction generally navigate through Access Database, get data fast, update data records by entering, update data and delete data. Run available report, use available forms, create simple forms and reports via wizards. This style tuition helps to maximise the value that you get from the day.

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

SQL Queries Course, 1-Day. Basic SQL syntax. This course is good for any database, covering standard SQL. Most attendees are in-work IT Professional. Private individuals are also very welcome.

Test d’Evaluation de Français (TEF) or Test de Connaissance du Français (TCF) Preparation Course (8 Hours – One-to-One Coaching)