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In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Graph Theory Basics is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Graph Theory Basics and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 10 hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Course Promo Graph Theory Promo 00:02:00 Module 01: Supplements Textbook Recommendations 00:02:00 Tools and Softwares 00:05:00 Sets 00:09:00 Number Sets 00:10:00 Parity 00:12:00 Terminologies 00:07:00 Module 02: Fundamentals Introduction 00:03:00 Graphs 00:11:00 Subgraphs 00:09:00 Degree 00:10:00 Sum of Degrees of Vertices Theorem 00:23:00 Adjacency and Incidence 00:09:00 Adjacency Matrix 00:16:00 Incidence Matrix 00:08:00 Isomorphism 00:08:00 Module 03: Paths Introduction 00:01:00 Walks, Trails, Paths, and Circuits 00:13:00 Examples 00:10:00 Eccentricity, Diameter, and Radius 00:07:00 Connectedness 00:20:00 Euler Trails and Circuits 00:18:00 Fleury's Algorithm 00:10:00 Hamiltonian Paths and Circuits 00:06:00 Ore's Theorem 00:14:00 Dirac's Theorem 00:06:00 The Shortest Path Problem 00:16:00 Module 04: Graph Types Introduction 00:01:00 Trivial, Null and Simple Graphs 00:10:00 Regular Graphs 00:10:00 Complete, Cycles and Cubic Graphs 00:10:00 Path, Wheel and Platonic Graphs 00:11:00 Bipartite Graphs 00:14:00 Module 05: Trees Introduction 00:01:00 Trees 00:14:00 Cayley's Theorem 00:03:00 Rooted Trees 00:10:00 Binary Trees 00:14:00 Binary Tree Traversals 00:18:00 Binary Expression Trees 00:09:00 Binary Search Trees 00:19:00 Spanning Trees 00:10:00 Forest 00:07:00 Module 06: Digraphs and Tournaments Introduction 00:01:00 Digraphs 00:12:00 Degree 00:09:00 Isomorphism 00:08:00 Adjacency Matrix 00:10:00 Incidence Matrix 00:05:00 Walks, Paths and Cycles 00:12:00 Connectedness 00:05:00 Tournaments 00:08:00 Module 07: Planar Graphs Introduction 00:01:00 Planar Graphs 00:10:00 Kuratowski's Theorem 00:14:00 Euler's Formula 00:10:00 Dual Graphs 00:11:00 Module 08: Graph Operations Introduction 00:01:00 Vertex and Edge Deletion & Addition 00:08:00 Cartesian Product 00:10:00 Graph Join and Transpose 00:04:00 Complement Graphs 00:05:00 Module 09: Graph Colourings Introduction 00:01:00 Vertex Colourings 00:05:00 Edge Colourings 00:09:00 Total Colourings 00:05:00

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SMTP training course description A hands on course focusing on the workings of email systems and the standard protocols that they use. The course is not specific to any particular implementation, but some vendor specifics are noted. Linux and Microsoft machines are used in hands on sessions to reinforce the theory of major sessions. The course concentrates on troubleshooting and interworking using network sniffing and protocol inspection rather than "which buttons to push". What will you learn Describe and explain SMTP MIME POP3 IMAP PGP, GPG, S/MIME SPF, DKIM, DMARC Configure mail routing Secure email systems SMTP training course details Who will benefit: Technical staff responsible for email systems. Prerequisites: TCP/IP foundation for engineers. Duration 3 days SMTP training course contents SMTP architecture What is SMTP, email before SMTP, SMTP history, the different protocols, clients, servers. Email composition, transmission, delivering emails, storing and reading emails. MUAs, MTAs, POP3, IMAP, SMTP, DNS, webmail. Hands on Setting up MTAs and MUAs and sending a simple email using telnet. The SMTP protocol SMTP protocol stack, SMTP headers, HELO, SMTP mail, MAIL FROM, RCPT TO, DATA, SMTPUTF8, 8BITMIME, TURN, EHLO, ETRN, 3 digit replies. Hands on Analysing SMTP packets on a network. DNS and SMTP SMTP forwarding, SMTP relays, interoperation, how SMTP uses DNS, MX records. Hands on Setting up mail relays. SMTP headers IMF data, From, to, cc, bcc, sender and recipient headers, message Ids, received trails, in-reply-to, received-SPF, mail list headers. Hands on Using clients to analyse details from mail headers, including true originators and path of emails. MIME Email attachments, MIME versions, content type headers, encoding, base 64, binary data, multi part headers, troubleshooting attachments. Hands on Analysing MIME headers and attachments. POP3 What is POP3, where to use POP3, authorisation, transactions, POP3 commands: USER, PASS, STAT, LIST, RETR, DELE. Hands on Setting up a POP3 server, analysing POP3 packets on a network. IMAP and IMAPS What is IMAP, where to use IMAP, authorisation, mailbox structure, IMAP commands: LOGIN, AUTHENTICATE, LIST, CREATE, Examine (message flags), SELECT, STORE. Hands on Setting up an IMAP server and analysing IMAP packets on a network. Interoperation Mail gateways, addressing, Exchange, sendmail. Email security Basics, Transport level: STARTTLS. Content: PGP/GPG, mail signing and encryption, S/MIME, digital certificates, secure email submission. Hands on Setting up and using a PGP key, configure MTAs to use TLS. Email authentication and spam prevention Mail relays, grey listing, block list & RBL, DNSBL (Real-time Black hole List), White list, SPF, Domain Keys Identified Mail (DKIM), Author Domain Signing Practices (ADSP), Abuse Report Format (ARF), Domain-based Message Authentication, Reporting and Conformance (DMARC). Hands on Relay spamming and the blocking spamming.

Machine learning is a vital aspect of data science, and it is the fundamental building block of artificial intelligence. This course is designed to help you master the basics of machine learning by taking you through ten comprehensive modules. Learning outcomes: Understand the basic principles of machine learning and its significance in today's world. Learn how to use Minitab for data analysis and data cleaning. Understand how regression trees and classification trees work and how to apply them. Understand binary logistic regression and its applications. Understand data modelling and how to use different predictors. Learn how to evaluate and improve the performance of machine learning models. The Machine Learning Basics course is designed to help individuals develop a fundamental understanding of machine learning. In this course, you will learn about the basics of machine learning, including regression, predictors, data cleaning, and data models. Additionally, you will learn how to use Minitab for data analysis and how to apply binary logistic regression, regression trees, and classification trees. The course includes ten comprehensive modules that will help you develop the skills you need to become a machine learning expert. This course is for anyone who wants to learn the basics of machine learning, including students, data analysts, and business professionals. By the end of the course, you will have a deep understanding of machine learning principles, including how to apply machine learning algorithms to solve real-world problems. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Students who want to learn about machine learning. Data analysts who want to enhance their skills. Business professionals who want to understand machine learning. Anyone who wants to develop a fundamental understanding of machine learning. Career path Career paths related to this industry are: Data analyst: £20,000 - £50,000 per year Machine learning engineer: £30,000 - £90,000 per year Data scientist: £35,000 - £80,000 per year Business intelligence analyst: £25,000 - £55,000 per year Artificial intelligence (AI) specialist: £45,000 - £100,000 per year Software engineer: £25,000 - £70,000 per year

The Computer Science and Programming Diploma course covers the fundamental theories of Algorithm Analysis. If you want to explore the concepts and methods that make a good programmer, then the course is designed for you. Programming is all about how to solve a problem. Programming theory is not confined to a single language; rather it applies to all programming languages. By understanding the right programming theory, you will be able to analyse a problem and also able to find out the probable solution. The course teaches you these Programming theories covering Algorithm analysis, Binary Number System, Arrays and their Advantages, the process of analysing a problem, Nodes and their Importance, various sorting algorithms and their comparisons, and more. Upon completion, you will be able to understand the core theories of computer science. What Will I Learn? Understand the Fundamental Theories of Algorithm Analysis Be able to Compare Various Algorithms Understand When to use Different Data Structures and Algorithms Understand the Fundamentals of Computer Science theory Requirements A Willingness to Learn New Topics! No Prior Experience or Knowledge is Needed! Module: 01 Kurt Anderson - 1 Introduction FREE 00:01:00 Kurt Anderson - 2 Binary System FREE 00:11:00 Kurt Anderson - 3 Complexity Introduction 00:02:00 Kurt Anderson - 4 Math Refresher Logarithmic Functions 00:11:00 Kurt Anderson - 5 Math Refresher Factorial Functions.TS 007 00:03:00 Kurt Anderson - 6 Math Refresher Algebraic Expressions.TS 00:03:00 Kurt Anderson - 7 n-notation 00:19:00 Kurt Anderson - 8 Big O 00:13:00 Kurt Anderson - 9 Big O Real World Example 00:10:00 Module: 02 Kurt Anderson - 10 How is Data Stored 00:09:00 Kurt Anderson - 11 Fixed Arrays 00:20:00 Kurt Anderson - 12 Circular Arrays 00:08:00 Kurt Anderson - 13 Dynamic Arrays 00:16:00 Kurt Anderson - 14 Array Review 00:08:00 Kurt Anderson - 15 Array Real World Examples 00:06:00 Kurt Anderson - 16 Linked List 00:12:00 Kurt Anderson - 16 Nodes 00:04:00 Kurt Anderson - 17 Linked List Run Times 00:15:00 Kurt Anderson - 18 Doubly Linked Lists 00:08:00 Kurt Anderson - 19 Tail Pointer 00:05:00 Module: 03 Kurt Anderson - 20 Linked List Real World Examples 00:03:00 Kurt Anderson - 20 Stack Example 00:11:00 Kurt Anderson - 21 Linked List Review 00:04:00 Kurt Anderson - 22 Stacks 00:10:00 Kurt Anderson - 23 Queues 00:09:00 Kurt Anderson - 24 Queue Examples 00:10:00 Kurt Anderson - 25 Queue and Stack Run Times 00:06:00 Kurt Anderson - 26 Stack and Queues Real World Examples 00:07:00 Kurt Anderson - 27 Sorting Algorithm Introdcution 00:02:00 Kurt Anderson - 28 Bubble Sort 00:10:00 Kurt Anderson - 29 Selection Sort 00:10:00 Module: 04 Kurt Anderson - 30 Insertion Sort 00:09:00 Kurt Anderson - 31 Quick Sort 00:15:00 Kurt Anderson - 32 Quick Sort Run Times 00:10:00 Kurt Anderson - 33 Merge Sort 00:12:00 Kurt Anderson - 34 Merge Sort Run Times 00:08:00 Kurt Anderson - 35 Stable vs Nonstable 00:07:00 Kurt Anderson - 36 Sorting Algorithm Real World Examples 00:04:00 Kurt Anderson - 37 Basics of Trees 00:08:00 Kurt Anderson - 38 Binary Search Tree 00:09:00 Kurt Anderson - 39 BST Run Times 00:08:00 Module: 05 Kurt Anderson - 40 Tree Traversals 00:13:00 Kurt Anderson - 41 Tree Real World Examples 00:05:00 Kurt Anderson - 42 Heap Introduction 00:04:00 Kurt Anderson - 43 Heap Step by Step 00:12:00 Kurt Anderson - 44 Heap Real World Examples 00:07:00 Kurt Anderson - 45 Thank You 00:01:00

Master the intricacies of digital electric circuits and intelligent electrical devices with our comprehensive Electrical Engineering course. Gain practical skills and theoretical insights to excel in this dynamic field.

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.