104 Programming courses in Borehamwood

For pupils aged 14+ | Delivered in UK Schools by Real World App and Games Developers Our new Getting Started with Website Design and Development Workshop is a great way to introduce your pupils to coding. We’ll focus on HTML, CSS and JavaScript throughout a full-day workshop. At the end of the day, they will have a working website, along with notes and support so they are equipped to design an online portfolio for their work, or other project.

Practical SQL Advanced Intensive Course , exploring the advanced and less commonly used SQL Statements and techniques. We also learn Data Definition Language and Data Manipulation Language statements. as well as course automation of queries using T-SQL. Hands-on, Practical SQL Advanced Course. PCWorkshops SQL Advanced Course Certificate. Max 4 people per course; we keep it personalised.

For pupils aged 9 - 16 | Delivered in UK Schools by Real World App and Games Developers Our micro:bit Workshop teaches your class about the micro:bit, making some apps and games with them during the workshop (we bring our own micro:bits too if your school doesn't yet have any!). We’ll introduce them to MakeCode, the coding language that the micro:bit uses, and teach them the fundamentals of coding before we work on some really fun projects! For older students, we can even use Python with the micro:bit!

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Many organisations find that project teams struggle to create and maintain effective plans. Estimates are often overly optimistic and risks go unmanaged until the inevitable happens. Resource managers also find it hard to forecast the likely loading on their departments and requests for support are not provided in a consistent format. This programme has been developed to address these needs in a very practical, hands-on format. Case study work can be based on simulations or on the organisation's current projects for maximum benefit to participants. The aim of this training is to develop and enhance participants' planning and risk management skills in order to maximise the success of project work undertaken by the organisation. The principal training objectives for this programme are to: Provide a structured, integrated approach to planning and risk management Demonstrate practical tools and techniques for each stage of planning Show how to organise and involve relevant people in the planning process Explain how to use the plan for forecasting and pro-active project control Identify ways to improve planning, both individually and corporately The course will emphasise the importance of participative planning techniques that improve the quality of plans whilst reducing overall time and cost of planning. The course will encourage discussion of internal procedures and practices and may be customised to include them if required. DAY ONE 1 Introduction (Course sponsor) Why this programme has been developed Review of participants' needs and objectives 2 Projects and planning Why plan? The benefits of good planning / penalties of poor planning Planning in the project lifecycle; the need for a 'living' plan The interaction between target setting and the planning process Team exercise: planning the project 3 Planning the plan Defining the application and structure of the plan Impact of planning decisions during the project lifecycle Using available time to create an effective plan 4 Defining deliverables Assessing the context; reviewing the goals and stakeholders Developing the scope and defining deliverables; scope mapping Understanding customer priorities; delivering value for money Case study: defining the project deliverables 5 Creating the work breakdown Building the work breakdown structure Detailing the tasks and sub-tasks; structured brainstorming Defining task ownership; the task responsibility matrix 6 Creating and using a logical network Developing the logical network; task boarding Determining the critical path and calculating float Accelerating the plan; concurrent programming and risk Individual and group exercises DAY TWO 7 Developing resource schedules Deriving the Gantt chart from the network Developing the detailed resource schedules Calculating the expenditure profile ('S' curve) 8 Estimating task durations and costs Understanding estimates: effort, availability and duration Estimating tools and techniques Application of estimating techniques during the project lifecycle 9 Case study Developing the project plan Refining the project plan Team presentations and discussion 10 Managing risks and refining the plan Awareness of contractual issues associated with risk Identifying and evaluating risks; deciding ownership Managing risks: determining levels of provision and contingency Controlling risks: maintaining an up-to date risk register 11 Planning for pro-active control The earned value analysis (EVA) concept and its predictive value Deriving the measures needed for cost and delivery performance Practical issues associated with implementing EVA 12 Using and maintaining the plan Tracking progress and updating the plan Publishing and controlling the plan 13 Course review and transfer planning (Course sponsor present) Identify ways of implementing the techniques learnt Sponsor-led review and discussion of proposals Conclusion

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.

Code the Hangman Game in a few hours, in our Taster Java Hangman Code course Basics made simple! Learn plenty in one day and apply techniques to a game by coding The Hangman Game. Get to know what is Java coding. Will you enjoy a coding career? Or for coders, simply fast-track crossing over to Java.

Python Unittest Course Summary. Testing plays a major role in software development. This course will explain Python Unit Testing using the unittest built-in module. We'll cover issues before going to the production itself and the basics of testing in Python. Location: Instructor-led, Online. Our Style: Hands-on, Practical Course. Group Size: Max 4 people per group. Qualification: PCWorkshops Unittest Certification Duration: 1-Day, 10am-5pm Unittest topics UnitTest Framework - Home UnitTest Framework - Overview UnitTest - Framework UnitTest - API UnitTest - Assertion UnitTest - Test Discovery UnitTest - Skip Test UnitTest - Exceptions Test UnitTest - Time Test UnitTest - Unittest2 UnitTest - Signal Handling UnitTest - Doctest UnitTest - Doctest API UnitTest - Py.test Module Nose Testing - Framework Nose Testing - Tools Included with Python Unittest Course Python Unittest Certificate on completion Python Unittest Videos Python Unittest Notes Python Unittest Examples Practical Python Unittest exercises

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