440 Engineering courses in Cheshunt delivered Live Online

This Renewables Technical Surveying training short two day course is specifically designed for individuals and companies that want to train themselves and their staff on exactly how to carry out Renewables Technical Site Surveying prior to any renewables installation measures, this includes for heating systems, solar systems and EV Charge point installations. The course is primarily aimed at Energy Suppliers, Equipment Manufacturers, Renewable Installers, Domestic Energy Assessors, Retrofit Assessors, Retrofit Co-ordinators, Renewables sales staff and suitable individuals with a basic level of knowledge in varying building structures, heating systems and varying renewable technologies.

How to Analyse & Maximize Restaurant Profits Course Overview This course on "How to Analyse & Maximize Restaurant Profits" offers comprehensive insights into understanding the financial dynamics of a restaurant business. It covers key concepts such as revenue analysis, menu optimisation, and cost control strategies to help learners identify areas of improvement for enhanced profitability. By the end of the course, learners will have a thorough understanding of the various factors influencing restaurant performance, from pricing strategies to inventory management. This course provides valuable skills that enable learners to make informed decisions that directly impact the bottom line of any restaurant business. Course Description In this course, learners will explore essential topics such as restaurant revenue analysis, menu engineering, and cost management. The course delves into the principles of profit maximisation, offering strategies to analyse sales data, optimise menu offerings, and manage food and labour costs efficiently. Learners will acquire skills in identifying profitable menu items, reducing waste, and increasing operational efficiency. This in-depth course is designed to equip participants with the knowledge and strategies needed to improve the profitability of a restaurant, ensuring they can make data-driven decisions to drive growth and sustainability. How to Analyse & Maximize Restaurant Profits Curriculum Module 01: Introduction Module 02: Restaurant Revenue Analysis Module 03: Menu Engineering Report Module 04: Cost Analysis & Management (See full curriculum) Who is this course for? Individuals seeking to understand restaurant profitability. Professionals aiming to enhance their skills in restaurant management. Beginners with an interest in the food and hospitality industry. Entrepreneurs looking to improve restaurant financial performance. Career Path Restaurant Manager F&B (Food and Beverage) Operations Manager Menu Analyst Financial Analyst in the hospitality industry Restaurant Owner/Entrepreneur

This Digital Electronics Course is designed to give practical knowledge of the type of electronic circuitry used in a modern Computer System or in any type of Computer Controlled equipment such as Photocopiers, Cash Registers, Tablets, mobile phones and many other types of IT equipment. Digital Electronics involves the use of Silicon chips (Integrated Circuits). The internal structure of a computer is to a large extent comprised of Digital Electronic Circuits.

Duration 70 Days 420 CPD hours Cisco Learning Library: Networking offers a subscription to all Cisco core online networking training, including product training, technology training, and certifications such as Cisco Routing and Switching, Wireless, Design, and Network Programmability.This comprehensive technical training library includes full-length, interactive certification courses, additional product and technology training with labs, and thousands of reference materials. Networking Library Certification Courses CCNA Implementing and Administering Cisco Solutions (CCNA) v1.0 CCNP Enterprise Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Designing Cisco Enterprise Wireless Networks (ENWLSD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 CCIE Enterprise Infrastructure Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 CCIE Enterprise Wireless Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Product and Technology Training Implementing and Administering Cisco Solutions (CCNA) v1.0 Developing Applications and Automating Workflows Using Cisco Core Platforms (DEVASC) v1.0 Developing Applications Using Cisco Core Platforms and APIs (DEVCOR) v1.0 Developing Solutions Using Cisco IoT and Edge Platforms (DEVIOT) v1.0 Implementing DevOps Solutions and Practices Using Cisco Platforms (DEVOPS) v1.0 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.0 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.0 Implementing Automation for Cisco Security Solutions (SAUI) v1.0 Implementing Automation for Cisco Service Provider Solutions (SPAUI) v1.0 Introducing Automation for Cisco Solutions (CSAU) v1.0 Cisco Certified Technician Supporting Cisco Routing and Switching Network Devices (RSTECH) v3.0 Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Cisco NCS 2000 Deploying 96-Channel Flex Spectrum (OPT201) v3.0 Cisco Digital Network Architecture Implementation Essentials (DNAIE) v2.0 Understanding Cisco Industrial IoT Networking Foundation (INFND) v1.0 Programming Use Cases for Cisco Digital Network Architecture v1.0 (DNAPUC) v1.0 Engineering Cisco Meraki Solutions Part 1 (ECMS1) v1.0 Deploying Cisco SD-Access (ENSDA) v1.1 Cisco SD-WAN Operation and Deployment (ENSDW) v1.0 Introduction to Cisco IOS XR (IOSXR100) v2.0 Cisco IOS XR System Administration (IOSXR200) v1.1 Cisco IOS XR Basic Troubleshooting (IOSXR201) v1.1 Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) v1.0 Cisco IOS XR Layer 3 VPN Implementation and Verification (IOSXR301) v1.1 Cisco IOS XRMulticast Routing Implementation and Verification (IOSXR302) v1.1 Cisco IOS XR Broadband Network Gateway Implementation and Verification (IOSXR304) v1.0 NSO Essentials for Programmers and Network Architects (NSO201) v3.0 Cisco NSO Administration and DevOps (NSO303) v3.0 Cisco Optical Technology Advanced (OPT300) v2.0 Implementing Segment Routing on Cisco IOS XR (SEGRTE201) v2.0 Operating and Implementing Cisco WAN Automation Engine (WAE200) v3.0 Implementing Cisco Virtual Wide Area Application Services (VWAAS) v1.0 Configuring and Operating Cisco EPN Manager (EPNM100) v3.0 Cisco Elastic Services Controller (ESC300) v2.0 Product and Technology Training Deploying Cloud Connect Solutions with Cisco Cloud Services Router 1000V (CLDCSR) v1.0 Implementing Cisco Multicast (MCAST) v2.0 Cisco Prime Central Intermediate ? Administration and Operations (CPCI-AO) v1.0 Cisco Prime Network Intermediate ? Administration and Operation (CPNI-AO) v1.1 Cisco Prime Provisioning (CPP) v6.5 Cisco Prime Performance Manager (CPPERF) v1.0 Implementing Cisco Catalyst 9000 Switches (ENC9K) v1.0 Cisco Aggregation Services Router 9000 Series Essentials (ASR9KE) v6.0 Network Convergence System 5500 Series Router (NCS5500HW) v1.0 Cisco DNA Center Fast-Start Use Cases (A-SDA-FASTSTART) Getting Started with DNA Center Assurance (A-DNAC-ASSUR) v1.0 Overview of Cisco DNA Center Fast Start Use Cases for System Engineers (P-SDA-SYSEF) Planning and Deploying SD-Access Fundamentals (For Customers) (CUST-SDA-FUND) v1.0 Preparing the Identity Services Engine (ISE) for SD-Access (For Customers) (CUST-SDA-ISE) v1.0 SD-Access 1.2 Update Supplement (A-SDA-12UPDT) The SD-WAN Mastery Collection - Getting Started (For Customers) v1.0 (A-SDW-START) The SD-WAN Mastery Collection - Deploying the Data Plane (For Customers) v1.0 (A-SDW-DATPLN) The SD-WAN Mastery Collection - Developing the Overlay Topology (For Customers) v1.0 (A-SDW-OVRLAY) The SD-WAN Mastery Collection - Managing the Application Experience (For Customers) v1.0 (A-SDW-APPEXP) The SD-WAN Mastery Collection - Bringing Up the Control Plane Devices (For Customers) v1.0 (A-SDW-CTRPLN) Securing Branch Internet and Cloud Access with Cisco SD-WAN (A-SDW-BRSEC) Programming for Network Engineers (PRNE) v1.0 Cisco Optical Technology Intermediate (OPT200) v2.0 Advanced Implementing and Troubleshooting MPLS VPN Networks (AMPLS) BGP Bootcamp (BGP) Building Core Networks with OSPF, IS-IS, BGP and MPLS Bootcamp (BCN) Configuring BGP on Cisco Routers (BGP) v4.0 Implementing Cisco MPLS v3.0 Internetworking Technology Overview (ITO) Introduction to IP Multicast Bootcamp Introduction to IPsec VPN Bootcamp (IPsec VPN) Introduction to IPv6 Bootcamp (IPv6) Introduction to MPLS-VPN Bootcamp (MPLS-VPN) LAN Switching Bootcamp (LAN-SW) RP Bootcamp Troubleshooting for Network Support Engineers

Energy Engineer Course Overview This Energy Engineer Course offers a comprehensive introduction to energy systems, focusing on both traditional and renewable sources. Learners will explore the history of energy consumption, understand key concepts of sustainable energy, and gain insight into various renewable technologies including solar, wind, and geothermal power. Designed to enhance technical knowledge and environmental awareness, this course equips learners with the skills to evaluate energy applications and contribute to eco-friendly solutions. By completing this course, participants will be prepared to support energy-efficient initiatives and advance their careers in energy engineering or related fields. Course Description The course covers a broad range of energy topics, from non-renewable fuels to cutting-edge renewable energy technologies such as fuel cells, ocean, and geothermal energy. Learners will examine the principles behind each energy type and the practical considerations involved in their application. The programme emphasises environmental responsibility, exploring how energy choices impact sustainability and ecological balance. Participants will develop critical thinking skills to assess energy systems and understand the role of engineers in promoting greener alternatives. This course is delivered through detailed content and case studies that deepen understanding and support career progression within the energy sector. Energy Engineer Course Curriculum Module 01: History of Energy Consumption Module 02: Non-Renewable Energy Module 03: Basics of Sustainable Energy Module 04: Fuel Cell Module 05: Solar Energy Module 06: Wind Energy Module 07: Ocean Energy Module 08: Geothermal Energy Module 09: Application of Renewable Energy Module 10: Being Environment-Friendly (See full curriculum) Who Is This Course For? Individuals seeking to build expertise in energy engineering and sustainability. Professionals aiming to enhance their career in energy management or environmental consulting. Beginners with an interest in renewable energy technologies and sustainable development. Engineers and technical staff wishing to update their knowledge of energy systems. Career Path Energy Engineer Renewable Energy Consultant Sustainability Analyst Environmental Project Manager Energy Systems Designer Green Building Specialist

Develop Big Data Pipelines with R, Sparklyr & Power BI Course Overview: This course offers a comprehensive exploration of building and managing big data pipelines using R, Sparklyr, and Power BI. Learners will gain valuable insight into the entire process, from setting up and installing the necessary tools to creating effective ETL pipelines, implementing machine learning techniques, and visualising data with Power BI. The course is designed to provide a strong foundation in data engineering, enabling learners to handle large datasets, optimise data workflows, and communicate insights clearly using visual tools. By the end of this course, learners will have the expertise to work with big data, manage ETL pipelines, and use Sparklyr and Power BI to drive data-driven decisions in various professional settings. Course Description: This course delves into the core concepts and techniques for managing big data using R, Sparklyr, and Power BI. It covers a range of topics including the setup and installation of necessary tools, building ETL pipelines with Sparklyr, applying machine learning models to big data, and using Power BI for creating powerful visualisations. Learners will explore how to extract, transform, and load large datasets, and will develop a strong understanding of big data architecture. They will also gain proficiency in visualising complex data and presenting findings effectively. The course is structured to enhance learners' problem-solving abilities and their competence in big data environments, equipping them with the skills needed to manage and interpret vast amounts of information. Develop Big Data Pipelines with R, Sparklyr & Power BI Curriculum: Module 01: Introduction Module 02: Setup and Installations Module 03: Building the Big Data ETL Pipeline with Sparklyr Module 04: Big Data Machine Learning with Sparklyr Module 05: Data Visualisation with Power BI (See full curriculum) Who is this course for? Individuals seeking to understand big data pipelines. Professionals aiming to expand their data engineering skills. Beginners with an interest in data analytics and big data tools. Anyone looking to enhance their ability to analyse and visualise data. Career Path: Data Engineer Data Analyst Data Scientist Business Intelligence Analyst Machine Learning Engineer Big Data Consultant

Power Analysis in AC Circuits Course Overview This course on Power Analysis in AC Circuits provides a comprehensive exploration of the principles and calculations essential for understanding power in alternating current systems. Learners will gain a solid grasp of real, reactive, and complex power, along with power factor correction and the analysis of power in three-phase circuits. The course emphasises the theoretical foundations and mathematical techniques necessary for accurate power analysis. By completing this course, students will be equipped to evaluate and optimise AC power systems effectively, enhancing their technical competence for roles in electrical engineering, energy management, and related fields. Course Description This course delves deeply into the concepts and calculations related to power in AC circuits, starting from fundamental definitions to advanced power factor correction and three-phase power analysis. Topics include power and energy definitions, the behaviour of power in reactive circuits, power trigonometrical identities, and the interpretation of complex power. Learners will develop skills in analysing real and reactive power components and understanding their impact on circuit efficiency. Additionally, the course covers methods to improve power factor and explores power dynamics in three-phase systems. Throughout, emphasis is placed on theoretical understanding and analytical methods to equip learners with the expertise to assess and manage AC power circuits in professional settings. Power Analysis in AC Circuits Curriculum Module 01: Introduction Module 02: Power & Energy Defined Module 03: Power in Reactive Circuits Part A Module 04: Power in Reactive Circuits Part B Module 05: Power Trig Identities Module 06: Power, Real and Reactive Module 07: Power More on Average, Real & Reactive Module 08: Power – Complex Power Module 09: Power Factor Correction Module 10: Power in 3 Phase Circuits (See full curriculum) Who is this course for? Individuals seeking to understand and analyse power in AC electrical systems. Professionals aiming to enhance their knowledge of power factor correction and circuit efficiency. Beginners with an interest in electrical engineering and power systems. Technicians and engineers involved in energy management and electrical maintenance. Career Path Electrical Engineer Power Systems Analyst Energy Manager Electrical Design Engineer Electrical Maintenance Technician Renewable Energy Specialist

Develop the commercial awareness, financial knowledge and strategic thinking capabilities, to influence the direction of the business Course overview Duration: 2 days (13 hours) This course is aimed at managers who want to develop their commercial awareness, financial knowledge and strategic thinking capabilities, so that they can influence the direction of their business and deliver to their full potential. Day one of the course provides the skills and insights to make sense of your company’s financial position and performance. Day two helps delegates to consider the strategic thinking tools required to plot the forward course needed to maximise the potential of the business. As well as looking at how to make effective business decisions, this course gives a good grounding in finance and profitability. As a two day programme, day one provides the skills and insights to make sense of the company’s financial position and performance. Day two then considers the strategic thinking tools needed to plot the forward course needed to maximise the potential of the business. Objectives By the end of the course you will be able to: An understanding of the balance sheet, profit and loss account, cash flow and statutory and management accounts Learnt to correctly employment key financial ratios to analyse your business A practical definition of strategy analysis tools to examine the current environment and capabilities Steps to devise a mission and vision statement Recognition of the skills and resources needed to achieve the vision Generation of appropriate strategic and tactical commercial objectives Content What is Strategy Defining Strategy Strategic thinking Strategic models Commercial thinking – what is money? Where are we now STEEPLE analysis SWOT Analysis P&E forces at work Political distortions in capitalist markets Where are we trying to get to Setting the mission and vision Creating a BHAG Strategies for deflation and inflation The role of banks Commercial and investment banking Fractional reserving Securitisation How to get there Skill gap analysis Business Process Re engineering The role of creativity How to get there Getting the team on board Individual and team motivation The power of the brand Overcoming challenges Debt and deleveraging Change management Creating value Discounted Cash Flows Building the business case Asset Valuation techniques Making it happen Turning Strategic Thinking into Strategic Plans Scenario planning for an uncertain future Creating commitments and lock in Discussion and review Time will be set aside during the course for review sessions with time for questions, answers and action learning.

About this Virtual Instructor Led Certificate Training Course (VILT) Asset maintenance and equipment reliability teams play a significant role to ensure that there is no room for downtime and losses in production. They are often recognised for their contribution and ability to keep assets running productively in today's organisations. The Certificate in Asset Management Virtual Instructor Led Training (VILT) course will provide those involved in Asset Management with a full explanation of the key processes to manage assets across their lifecycle. This recognised VILT course has been designed to equip participants with practical skills to take back to work. This VILT course enables participants to ensure their organisation's assets are realising their full value in support of the organisation's objectives. Accredited by the Institute of Asset Management (IAM), this VILT course will prepare participants to sit for the IAM Asset Management Certificate qualification. The IAM exam is offered as an option for participants of this VILT course. Training Objectives By the end of this VILT course, participants will be able to: Understand the key principles, tools and terminology of Asset Management, and demonstrate how it will benefit your organisation Gain familiarity in the application of ISO 55000 in practice Access a range of models that will support the implementation of asset management in your organisation Assess your understanding of the current tools and concepts applied in Asset Management Capture new ideas and skills that will enhance performance and be better prepared for the Institute of Asset Management (IAM) Certificate Examination Target Audience This VILT course will benefit maintenance managers, operations managers, asset managers and reliability professionals, planners and functional specialists. It will also be useful for facilities engineers, supervisors/managers and structural engineers/supervisors/ and managers. IAM Qualifications Syllabi This document details the scope of the individual topics which comprise the examination modules, and how the exams are assessed. It is important that prospective candidates understand the scope of the modules to determine the preparation required. Download here IAM Qualifications Candidate Handbook This handbook provides more detailed information on registering as a candidate, learning resources, training courses, booking an exam, exam regulations and what happens after an exam - whether you are successful or unsuccessful. Download here Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 breaks of 15 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total) Other than world-class visuals and slides, this VILT course will include a high level of interaction between the facilitator and participants and group discussion among the participants themselves. There will be a number of exercises & quizzes to demonstrate key points and to give participants the chance to apply learning and appreciate key aspects of best practice. Participants will also have the chance to share examples from their own experience, discuss real problems they are facing and develop actions for improvement when they return to work. Examples of the exercises that are used in this VILT course are as follows: Exercises: Aligning Assets to Business Objectives, Planning for Contingencies, Understanding Function and Failure. Group exercises: Asset Management Decision Making, Incident Review & Operations Optimisation. The workshop content will be adjusted based on the discussions, interests and needs of the participants on the course. Trainer Your expert course leader is a is a highly experienced in maintenance and turnaround specialist. He is a Chartered Mechanical Engineer, having spent 19 years working for BP in engineering, maintenance and turnaround management roles. During this time, he worked on plants at all ages in the lifecycle, from construction, commissioning and operating new assets to maintaining aging assets and decommissioning. He has taken roles in Projects, Human Resources and Integrity Management which give real breadth to his approach. He also specialized in Continuous Improvement, gaining the award of International Petrochemical Coach of the year. He stays up to date with the latest industrial developments through his consulting support for major clients. He is also the Asset Management lead and a VILT specialist, having delivered over 70 days of VILT training in the last year. He has an engaging style and will bring his current industrial experience, proficiency of VILT techniques and diverse content, gathered from a comprehensive training portfolio, to deliver a distinctive training experience. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.