Getting Started The BSc in Health and Social Care is a comprehensive undergraduate program designed to equip students with the knowledge and skills necessary for success in the healthcare and social services sectors. This programme covers essential health, well-being, and social support topics, ensuring that graduates are well-prepared for fulfilling careers in these vital fields. Anglia Ruskin University offers the BSc (Hons) Health and Social Care program, a highly regarded undergraduate degree providing students with a deep understanding of the dynamic and crucial health and social care sectors. This program is tailored to equip students with the knowledge and skills essential for excelling in various roles within these sectors. The curriculum strongly emphasises integrating theory and practice, enabling students to develop the essential competencies required for effective healthcare and social work delivery. A standout feature of this program is its strong emphasis on real-world experience through placements and practical training, ensuring that graduates are well-prepared to tackle the challenges within the healthcare and social care sectors. Additionally, Anglia Ruskin University's distinguished reputation in healthcare education and research enhances the value of this program, making it an excellent choice for individuals aspiring to make a meaningful impact in these critical fields. The programme comprises two phases; the first is the Qualifi Level 4 and 5 Diploma in Health and Social Care, awarded by Qualifi and delivered by the School of Business and Technology London. The second phase is the BSc (Hons) Health and Social Care Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this programme. About Awarding Body Anglia Ruskin University began in 1858 as the Cambridge School of Art founded by William Beaumont. It was then merged with the Cambridge shire College of Arts and Technology and the Essex Institute of Higher Education and was renamed Anglia Polytechnic. It was then given university status in 1992 and renamed Anglia Ruskin University in 2005. The university has campuses in the UK (Cambridge, Chelmsford, London and Peterborough), as well as they are partnered with institutions around the world including Berlin, Budapest, Trinidad, Singapore and Kuala Lumpur. Assessment Assignments and Project No examinations Entry Requirements A Level or Equivalent Minimum 1 Year of Health and Social care work experience Further, candidates are also required to demonstrate their English language proficiency. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. Structure Phase 1 - Qualifi Level 4 and 5 Diploma in Health and Social Care Programme Structure Level 4 - Modules The QUALIFI Level 4 Diploma in Health and Social Care comprises 120 credits, equating to 1200 hours of TQT and 600 hours of GLH. The diploma requires six mandatory units at Level 4. Academic Study skills Reference No: T/505/9498 Credit: |20| TQT: 200 The primary objective of this unit is to equip individuals with the essential skills and knowledge required for effective higher education study, fostering the development of reflective and critical thinking abilities necessary for reaching their maximum learning potential and potentially advancing to the Level 5 Diploma in Health and Social Care. Communicating in Health and Social Care Reference No: H/505/9495 Credit: |20| TQT: 200 This unit aims to cultivate the learner's understanding of the various modes of communication utilised in health and social care settings and underscore their importance in ensuring efficient service delivery. An Introduction to Healthcare Policy Reference No : F/505/9505 Credit: |20| TQT: 200 This unit seeks to enhance the learner's awareness of the diverse factors influencing healthcare and their impact on policy development. Evaluating healthcare policies will enable learners to scrutinise the crucial contemporary concerns facing policy-makers, service providers, and support recipients. Reflective Practice Reference No : F/505/9519 Credit: |20| TQT: 200 Introducing learners to reflective practice in all its forms is the focus of this unit. Reflecting on and in practice holds significance in health and social care, promoting self-development and linking theoretical concepts to practical application. Managing people in Health and Social Care Reference No : L/505/9507 Credit: |20| TQT: 200 The primary objective of this unit is to provide learners with an understanding of the processes involved in the recruitment, management, and development of personnel in the health and social care workplace. Learners will investigate the procedures governing the management of individuals in this sector and explore how to instigate organisational change. Sociology: Concepts in Health and Social Care Reference No : M/505/9502 Credit: |20| TQT: 200 This unit aims to impart to learners an understanding of sociological concepts related to health and illness and their practical application in health and social care. It will enable learners to comprehend the nature of contemporary society and its influence on the perception of health and illness. Learners will delve into the structural aspects of culture, such as age, gender, ethnicity, social class, family, and households, and their impact on health and well-being. Level 5 - Modules The Level 5 Diploma is made up of 120 credits, which equates to 1200 hours of TQT and includes 500 hours of GLH. The Diploma requires five mandatory units at Level 5. Principles Underpinning Health and Social Care Reference No : K/505/9496 Credit: |20| TQT: 200 Health and social care professionals must adhere to specific ethical and professional standards. This course module is designed to foster comprehension of the principles, theories, and regulations that form the foundation of health and social care practice. It also explores the various tools and systems in place to uphold high standards of practice within the industry. The Management of Quality in Health and Social Care Reference No : A/505/9521 Credit: |20| TQT: 200 Quality plays a significant role in the realm of health and social care. In this unit, students will acquire insight into diverse viewpoints concerning the quality of health and social care services and the methods used to evaluate them. This knowledge aims to empower and involve service users in the process. Research Project Reference No : H/505/9500 Credit: |40| TQT: 400 The primary objective of this unit is to enhance students' research abilities, encouraging them to conduct a concise pilot study that directly pertains to their higher education program or career advancement. This endeavour aims to cultivate independent inquiry and critical analysis skills. Partnership working in Health and Social Care Reference No : A/505/9499 Credit: |20| TQT: 200 In this unit, students will grasp the significance of establishing favourable professional relationships in health and social care. The module will delve into the concept of partnership on three distinct levels: Collaboration with service users. Cooperation among health and social care practitioners. Engagement with organisations. Understanding these aspects will empower individuals to make informed choices and advocate for autonomy. Working with Service users with Complex Needs Reference No : T/505/9520 Credit: |20| TQT: 200 This course module aims to equip learners with insights into matters concerning health, disability, and illness. It further enables them to recognise effective strategies for assisting individuals with intricate physical and mental health requirements in their roles as healthcare professionals. Phase 2 - BSc (Hons) Health and Social Care Programme Structure Leadership Practice in Health and Social Care Evaluating Research for Evidence-Based Practice Strategic Management in Health and Social Care Undergraduate Major Project Delivery Methods The programme comprises two phases; the first is the Qualifi Level 4 and 5 Diploma in Health and Social Care, awarded by Qualifi and delivered by the School of Business and Technology London. The School of Business and Technology London offers flexible learning methods, including online and blended learning, allowing students to choose the mode of study that suits their preferences and schedules. The program is self-paced and facilitated through an advanced Learning Management System. Students can easily interact with tutors through the SBTL Support Desk Portal System for course material discussions, guidance, assistance, and assessment feedback on assignments. School of Business and Technology London provides exceptional support and infrastructure for online and blended learning. Students benefit from dedicated tutors who guide and support them throughout their learning journey, ensuring a high level of assistance. The second phase is the BSc (Hons) Health and Social Care Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this programme. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.
Our complete Certified Nursing Assistant Diploma course is expertly designed and features interactive lessons, real-world scenarios, and assessments to ensure you master all essential medical procedures and responsibilities with confidence.
Course Overview This Yoga Training course offers a comprehensive introduction to the principles, history, benefits, and diverse styles of yoga. Designed for learners of all backgrounds, the course provides a well-rounded understanding of yoga's evolution and its significant impact on physical and mental wellbeing. Participants will gain valuable insights into the therapeutic benefits of yoga, its philosophical foundations, and various styles practised globally today. Through clear and structured learning, this course highlights how yoga can contribute to improved balance, flexibility, mindfulness, and stress management. By the end of the training, learners will be well-equipped with essential theoretical knowledge, enabling them to pursue personal growth, introduce yoga into their daily routines, or take the first step towards a deeper exploration of this ancient discipline. Whether aiming for personal enrichment or professional development, this course offers practical value and inspiring outcomes for a diverse range of learners. Course Description Yoga Training: Benefits & Styles delves into the fascinating history, principles, and evolution of yoga, exploring its transformation from ancient spiritual practice to modern wellness discipline. Learners will study the key benefits of yoga, understand its influence on physical and mental health, and explore a variety of traditional and contemporary yoga styles. The course provides a structured overview, introducing different approaches to yoga, their unique features, and cultural significance. Through a carefully curated syllabus, learners will develop a firm understanding of foundational yoga concepts without needing any prior experience. Emphasis is placed on theoretical knowledge, enabling participants to appreciate yoga as a holistic practice that enhances body awareness, stress management, and mental clarity. Upon completion, learners will possess a strong knowledge base, preparing them for further exploration in yoga education or for applying yoga techniques meaningfully in personal or professional contexts. Course Modules Module 01: Introduction - Benefits - History Module 02: More On Yoga Module 03: Still More On Yoga Module 04: Conclusion (See full curriculum) Who is this course for? Individuals seeking to enhance their physical and mental wellbeing through yoga. Professionals aiming to expand their knowledge of holistic wellness practices. Beginners with an interest in understanding the foundations and styles of yoga. Enthusiasts wishing to incorporate yoga theory into personal development goals. Career Path Yoga Instructor (following further practical certification) Wellness Consultant Health and Lifestyle Coach Mindfulness Facilitator Corporate Wellness Adviser Holistic Therapy Assistant
Overview This Power Electronics for Electrical Engineering course will unlock your full potential and will show you how to excel in a career in Power Electronics for Electrical Engineering. So upskill now and reach your full potential. Everything you need to get started in Power Electronics for Electrical Engineering is available in this course. Learning and progressing are the hallmarks of personal development. This Power Electronics for Electrical Engineering will quickly teach you the must-have skills needed to start in the relevant industry. In This Power Electronics for Electrical Engineering Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Power Electronics for Electrical Engineering skills to help you advance your career. Acquire a comprehensive understanding of various Power Electronics for Electrical Engineering topics and tips from industry experts. Learn in-demand Power Electronics for Electrical Engineering skills that are in high demand among UK employers, which will help you to kickstart your career. This Power Electronics for Electrical Engineering course covers everything you must know to stand against the tough competition in the Power Electronics for Electrical Engineering field. The future is truly yours to seize with this Power Electronics for Electrical Engineering. Enrol today and complete the course to achieve a Power Electronics for Electrical Engineering certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Power Electronics for Electrical Engineering course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Power Electronics for Electrical Engineering course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate. Certificate of Achievement Upon successfully completing the Power Electronics for Electrical Engineering course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Power Electronics for Electrical Engineering is suitable for anyone aspiring to start a career in Power Electronics for Electrical Engineering; even if you are new to this and have no prior knowledge on Power Electronics for Electrical Engineering, this course is going to be very easy for you to understand. And if you are already working in the Power Electronics for Electrical Engineering field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. Taking this Power Electronics for Electrical Engineering course is a win-win for you in all aspects. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Power Electronics for Electrical Engineering course has no prerequisite. You don't need any educational qualification or experience to enrol in the Power Electronics for Electrical Engineering course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Power Electronics for Electrical Engineering course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Unit 1- Introduction to Power Electronics Components Module 1- Introduction to Power Electronics 00:13:00 Module 2- Uncontrolled Switches 00:17:00 Module 3- What is the Benefit of Diode 00:06:00 Module 4- Semi-Controlled Switches Part 1 00:09:00 Module 5- Semi-Controlled Switches Part 2 00:14:00 Module 6- Semi-Controlled Switches Part 3 00:05:00 Module 7- What is the Benefit of Thyristor 00:05:00 Module 8- Fully Controlled Switches Part 1 00:17:00 Module 9- Fully Controlled Switches Part 2 00:10:00 Module 10- Fully Controlled Switches Part 3 00:12:00 Unit 2- Fundamentals of Rectifier Circuits Module 1- Overview on Rectifiers 00:02:00 Module 2- Rectifier Definition 00:01:00 Module 3- Half Wave Uncontrolled Rectifier with R Load 00:21:00 Module 4- Example on Half Wave Uncontrolled Rectifier with R Load Part 1 00:06:00 Module 5- Example on Half Wave Uncontrolled Rectifier with R Load Part 2 00:07:00 Module 6- Half Wave Uncontrolled Rectifier with RL Load 00:10:00 Module 7- Derivation of the Discontinuous Current in R-L Load 00:08:00 Module 8- Freewheeling Diode (Commutation Diode) 00:03:00 Module 9- Half Wave R-L Load with FWD 00:09:00 Module 10- Difference Between Continuous and Discontinuous Mode in RL Load 00:07:00 Module 11- Half Wave RL Load with FWD Continuous Mode 00:06:00 Module 12- Example on Half Wave Rectifier with FWD 00:07:00 Module 13- Bridge Full Wave Uncontrolled Rectifier Part 1 00:07:00 Module 14- Bridge Full Wave Uncontrolled Rectifier Part 2 00:05:00 Module 15- Quick Revision on Bridge Full Wave Uncontrolled Rectifier 00:06:00 Module 16- Firing Angle 00:02:00 Module 17- Half Wave Controlled Rectifier R Load 00:05:00 Module 18- Half Wave Controlled Rectifier R-L Load 00:04:00 Module 19- Half Controlled R-L Load with FWD 00:06:00 Module 20- Example 1 00:07:00 Module 21- Example 2 00:08:00 Module 22- Example 3 00:13:00 Module 23- Example 4 00:09:00 Module 24- Example 5 00:05:00 Module 25- Fully Controlled Bridge Rectifier Part 1 00:06:00 Module 26- Fully Controlled Bridge Rectifier Part 2 00:06:00 Module 27- Quick Revision on Bridge Full Wave Controlled Rectifier 00:02:00 Module 28- Example 6 00:08:00 Module 29- Half Controlled Bridge Rectifier 00:08:00 Module 30- Half Controlled Bridge Rectifier with FWD 00:05:00 Module 31- Example 7 00:06:00 Module 32- Example 8 00:07:00 Module 33- Performance Parameters 00:04:00 Module 34- Power Factor 00:04:00 Unit 3- Fundamentals of AC Choppers Module 1- Introduction to AC Choppers 00:02:00 Module 2- Definition of AC Choppers 00:05:00 Module 3- Switching Techniques in AC Choppers 00:06:00 Module 4- Applications on AC Choppers 00:03:00 Module 5- Types of AC Choppers 00:02:00 Module 6- AC Chopper with R Load 00:14:00 Module 7- Example 1 on AC Chopper with R Load 00:06:00 Module 8- Example 2 on AC Chopper with R Load 00:04:00 Module 9- AC Chopper with L Load Part 1 00:13:00 Module 10- AC Chopper with L Load Part 2 00:06:00 Module 11- Example on AC Chopper with L Load 00:08:00 Module 12- AC Chopper with RL Series Load 00:20:00 Module 13- Example on AC Chopper with RL Series Load 00:07:00 Module 14- AC Chopper with RL Parallel Load 00:25:00 Module 15- Example on AC Chopper with RL Parallel Load 00:06:00 Module 16- AC Chopper with Pure Capacitive Load 00:14:00 Module 17- Example on AC Chopper with Pure Capacitive Load 00:04:00 Module 18- AC Chopper Loaded by Heavy Rectifier 00:06:00 Module 19- AC Chopper Loaded by an AC Motor with Sinusoidal Back Emf 00:12:00 Module 20- Example on AC Chopper Loaded by an AC Motor with Sinusoidal Back Emf 00:08:00 Module 21- Integral Cycle Control 00:11:00 Module 22- Example on Integral Cycle Control 00:04:00 Unit 4- Fundamentals of DC Choppers Module 1- Introduction to DC Choppers 00:02:00 Module 2- Definition and Application of DC Choppers 00:05:00 Module 3- Step down DC Chopper with R Load 00:12:00 Module 4- Example on Step Dwon DC Chopper with R Load 00:08:00 Module 5- Generation of Duty Cycle 00:09:00 Module 6- Switching Techniques 00:03:00 Module 7- Step Down DC Chopper with RLE Load Part 1 00:19:00 Module 8- Step Down DC Chopper with RLE Load Part 2 00:15:00 Module 9- Example 1 on Step Down DC Chopper with RLE Load 00:13:00 Module 10- Example 2 on Step Down DC Chopper with RLE Load 00:02:00 Module 11- Step Up DC Chopper with R or RL Load 00:09:00 Module 12- Step Up DC Chopper with RE Load 00:15:00 Module 13- Example on Step Up DC Chopper with RE Load 00:20:00 Module 14- Buck Regulator Part 1 00:16:00 Module 15- Buck Regulator Part 2 00:17:00 Module 16- Example on Buck Regulator 00:03:00 Module 17- Boost Regulator 00:23:00 Module 18- Example on Boost Regulator 00:06:00 Module 19- Buck Boost Converter 00:17:00 Module 20- Example on Buck-Boost Converter 00:05:00 Unit 5- Fundamentals of Inverters Module 1- Introduction to Inverters 00:02:00 Module 2- Definition of Inverters 00:04:00 Module 3- Importance and Applications of Inverters 00:08:00 Module 4- Single Phase Half Bridge R-Load 00:15:00 Module 5- Single Phase Half Bridge RL- Load 00:08:00 Module 6- Performance Parameters of an Inverter 00:05:00 Module 7- Example on Single Phase Half Bridge 00:10:00 Module 8- Single Phase Bridge Inverter R- Load 00:06:00 Module 9- Single Phase Bridge Inverter RL- Load 00:07:00 Module 10- Example on Single Phase Bridge Inverter 00:06:00 Module 11- Three Phase Inverters and Obtaining the Line Voltages 00:15:00 Module 12- Threee Phase Inverters and Obtaining The Phase Voltages 00:17:00 Module 13- Example on Three Phase Inverters 00:16:00 Module 14- Single Pulse Width Modulation 00:13:00 Module 15- Multiple Pulse Width Modulation 00:13:00 Module 16- Example on Multiple Pulse Width Modulation 00:04:00 Module 17- Sinusoidal Pulse Width Modulation 00:16:00 Module 18- Industrial Inverter 00:03:00
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Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights. Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00
Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. Acquire a comprehensive understanding of various Deep Learning & Neural Networks Python - Keras: For Dummies topics and tips from industry experts. Learn in-demand Deep Learning & Neural Networks Python - Keras: For Dummies skills that are in high demand among UK employers, which will help you to kickstart your career. This Deep Learning & Neural Networks Python - Keras: For Dummies course covers everything you must know to stand against the tough competition in the Deep Learning & Neural Networks Python - Keras: For Dummies field. The future is truly yours to seize with this Deep Learning & Neural Networks Python - Keras: For Dummies. Enrol today and complete the course to achieve a Deep Learning & Neural Networks Python - Keras: For Dummies certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Deep Learning & Neural Networks Python - Keras: For Dummies course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Deep Learning & Neural Networks Python - Keras: For Dummies course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate. Certificate of Achievement Upon successfully completing the Deep Learning & Neural Networks Python - Keras: For Dummies course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Deep Learning & Neural Networks Python - Keras: For Dummies is suitable for anyone aspiring to start a career in Deep Learning & Neural Networks Python - Keras: For Dummies; even if you are new to this and have no prior knowledge on Deep Learning & Neural Networks Python - Keras: For Dummies, this course is going to be very easy for you to understand. And if you are already working in the Deep Learning & Neural Networks Python - Keras: For Dummies field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. Taking this Deep Learning & Neural Networks Python - Keras: For Dummies course is a win-win for you in all aspects. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Deep Learning & Neural Networks Python - Keras: For Dummies course has no prerequisite. You don't need any educational qualification or experience to enrol in the Deep Learning & Neural Networks Python - Keras: For Dummies course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Deep Learning & Neural Networks Python - Keras: For Dummies course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00
Overview of Dog Training - Stop Dog Attacks Are you worried about dog attacks—whether from your own pet or another dog? The Dog Training - Stop Dog Attacks Course is designed to help you stay safe and build a better bond with dogs. Every year, around 250,000 people in the UK are bitten by dogs. In fact, hospital visits due to dog attacks have gone up by 17% in recent years. This course helps you understand dog behaviour, especially signs that show if a dog is feeling aggressive or scared. You’ll learn how to react the right way to stop problems before they happen. This is more than basic obedience training. The Dog Training - Stop Dog Attacks Course goes deeper by showing you the real reasons behind dog aggression. You’ll learn how to spot warning signs and calm things down before a dog reacts. The course also shows how to handle leash-pulling, prevent fights between dogs, and guide aggressive dogs in safe ways. These are skills you can use every day with your dog or any dog you meet. Many people have already seen big changes using this course. It helps build trust, respect, and understanding between dogs and humans. With the Dog Training - Stop Dog Attacks Course, you’ll be ready to create a safer and more peaceful life with your dog. This Dog Training - Stop Dog Attacks course will help you to learn: Spot the difference between confident and scared behaviour in dogs. Use calm and strong leadership to guide your dog’s behaviour. Stop your dog from pulling on the leash during walks. Notice early signs that a dog may be ready to attack. Help aggressive dogs mix safely with other dogs. Use simple steps to stop aggressive behaviour from happening again. Who is this Course for? Dog owners who have trouble with their pet’s aggression and want real help to stop attacks. Dog walkers who look after more than one dog and want to feel safer when handling aggressive dogs. Rescue centre workers who care for dogs with past trauma or social problems. Pet owners who’ve gone through a dog attack and want to understand why it happened and how to prevent it. Puppy owners who want to teach their dog the right behaviour from the start. Process of Evaluation After studying the Dog Training - Stop Dog Attacks Course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Dog Training - Stop Dog Attacks Course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. (Each) Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Requirements There is no prerequisite to enrol in this course. Career path Dog Behaviour Expert – Earn around £25,000 to £45,000 a year Dog Trainer – Earn around £20,000 to £35,000 a year Animal Welfare Worker – Earn around £18,000 to £28,000 a year Dog Walker or Handler – Earn around £15,000 to £25,000 a year Dog Rehabilitation Therapist – Earn around £22,000 to £38,000 a year Course Curriculum The Proof Is In The Pudding - This Is What People Say Why Getting 2, 8 Week Old Parson Terrier Puppies Changed My Life And My Career! 00:03:00 This Is What People Say Who've Learnt My Methods 00:01:00 This Could Be You! 00:15:00 This is What You'll Get from This Course Able To Do All This After the Course... 00:04:00 Important - Please Read This Before Starting The Course Important - Please Read This First 00:05:00 Challenging And Submissive Signals In Dogs How To Recognize Challenging And Submissive Signs In Order to Stop an Attack 00:11:00 Body Language And How To Get Leadership qualities 00:07:00 Pulling on the Leash and Dog Aggression The Missing Part of Dog Aggression - You Must Get This Right First 00:10:00 How To Get Your Dog To Walk Calmly On The Leash And Integrate Aggressive Dogs 00:08:00 Who's Walking Who E-Book 01:00:00 This Video Shows You How To Get An Aggressive Dog To Relax Around Other Dogs 00:05:00 A Dog Attack What A Dog Attack Means And How To Stop It Happening Again 00:15:00 The Transcript To Lectures 6,7 And 10 00:10:00 Mock Exam Mock Exam - Dog Training - Stop Dog Attacks 00:20:00 Final Exam Final Exam - Dog Training - Stop Dog Attacks 00:20:00
Embarking on the CompTIA Security+ course is akin to unlocking a treasure trove of cybersecurity knowledge. Imagine standing at the forefront of digital security, equipped with the latest tools and techniques to safeguard information systems. This course, meticulously designed with fourteen comprehensive sections, offers an immersive journey from the basics of risk management to the complexities of securing dedicated systems. The curriculum is tailored to blend theoretical knowledge with real-world applications, ensuring learners grasp the essence of cybersecurity in today's technology-driven world. Whether it's understanding the nuances of cryptography or mastering the art of incident response, CompTIA Security+ is your gateway to becoming a cybersecurity connoisseur. Delving into this course, you'll navigate through a landscape where every section is a stepping stone to mastering security competencies. The course begins with an introduction to the fundamental principles of cybersecurity, setting the stage for more advanced topics like identity and account management, and securing wireless LANs. Each section is a meticulously crafted module, aimed at building a robust understanding of both the threats and the defenses in the cyber world. By the time you reach the final sections on secure protocols, applications, and testing infrastructure, you will have developed a holistic view of network security, ready to apply your knowledge in a variety of real-world scenarios. CompTIA Security+ is not just a course; it's a journey through the dynamic landscape of network security. As you progress from one section to another, you'll not only learn about securing individual systems and public servers but also about the importance of physical security in protecting digital assets. This course is a blend of theory and practicality, providing an in-depth understanding of the latest security tools and techniques. It's an opportunity to transform yourself into a sought-after professional in the cybersecurity domain, equipped with the knowledge to protect and defend against the ever-evolving cyber threats. Learning Outcomes Develop a comprehensive understanding of risk management strategies and their application in cybersecurity. Acquire proficiency in various cryptographic methods and their importance in securing data. Gain insights into effective identity and account management to enhance system security. Learn to utilize essential security tools for safeguarding individual and network systems. Master the skills to implement and manage security measures for both wired and wireless networks. Why buy this CompTIA Security+? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the CompTIA Security+ there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Individuals aiming to start a career in cybersecurity. IT professionals seeking to deepen their knowledge in network security. System administrators wanting to enhance their security skills. Students interested in acquiring a foundational understanding of cybersecurity principles. Professionals aiming to achieve the CompTIA Security+ certification for career advancement. Prerequisites This CompTIA Security+ does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Security+ was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Cybersecurity Analyst: £30,000 - £60,000 annually Information Security Manager: £40,000 - £75,000 annually Network Security Engineer: £35,000 - £65,000 annually Security Consultant: £35,000 - £70,000 annually Systems Administrator (with security specialization): £25,000 - £50,000 annually IT Security Coordinator: £28,000 - £55,000 annually Course Curriculum Section 01: Introduction Introduction to CompTIA Security+ SY0-601 00:03:00 About the CompTIA Security+ SY0-601 Exam 00:03:00 Section 02: Risk Management Defining Risk 00:08:00 Threats and Vulnerabilities 00:07:00 Threat Intelligence 00:11:00 Risk Management Concepts 00:07:00 Security Controls 00:09:00 Risk Assessments and Treatments 00:06:00 Quantitative Risk Assessments 00:07:00 Qualitative Risk Assessments 00:04:00 Business Impact Analysis 00:05:00 Data Types and Roles 00:11:00 Security and the Information Life Cycle 00:09:00 Data Destruction 00:06:00 Personnel Risk and Policies 00:10:00 Third-Party Risk Management 00:09:00 Agreement Types 00:07:00 Exam Question Review 00:02:00 Wiping Disks with the dd Command Lab 00:06:00 Ask Me Anything (AMA) 00:02:00 Section 03: Cryptography Cryptography Basics 00:16:00 Data Protection 00:09:00 Cryptographic Methods 00:07:00 Symmetric Cryptosystems 00:13:00 Symmetric Block Modes 00:08:00 Asymmetric Cryptosystems 00:13:00 Diffie-Hellman 00:07:00 Hashing 00:09:00 Understanding Digital Certificates 00:08:00 Trust Models 00:05:00 Public Key Infrastructure 00:04:00 Certificate Types 00:14:00 Touring Certificates 00:09:00 Cryptographic Attacks 00:05:00 Password Cracking 00:10:00 Password Cracking Demo 00:06:00 Exam Question Review 00:02:00 SSH Public Key Authentication Lab 00:09:00 Ask Me Anything (AMA) 00:02:00 Section 04: Identity and Account Management Identification, Authentication, and Authorization 00:08:00 Enabling Multifactor Authentication 00:05:00 Authorization 00:05:00 Accounting 00:05:00 Authentication Methods 00:14:00 Access Control Schemes 00:07:00 Account Management 00:13:00 Network Authentication 00:09:00 Identity Management Systems 00:06:00 Exam Question Review 00:02:00 Creating LInux Users and Groups Lab 00:06:00 Ask Me Anything (AMA) 00:01:00 Section 05: Tools of the Trade Touring the CLI 00:16:00 Shells 00:06:00 The Windows Command Line 00:05:00 Microsoft PowerShell 00:13:00 Linux Shells 00:12:00 Python Scripts 00:06:00 Windows Command-Line Tools 00:16:00 Linux Command-Line Tools 00:10:00 Network Scanners 00:05:00 Network Scanning with Nmap 00:09:00 Network Protocol Analyzers 00:08:00 Using Wireshark to Analyze Network Traffic 00:09:00 Using tcpdump to Analyze Network Traffic 00:08:00 Log Files 00:09:00 Centralized Logging 00:09:00 Configuring Linux Log Forwarding 00:08:00 Exam Question Review 00:03:00 Lunux Shell Script Lab 00:07:00 Nmap Lab 00:05:00 Ask Me Anything (AMA) 00:02:00 Section 06: Securing Individual Systems Malware 00:14:00 Weak Configurations 00:12:00 Common Attacks 00:09:00 Driver and Overflow Attacks 00:08:00 Password Attacks 00:08:00 Bots and Botnets 00:06:00 Disk RAID Levels 00:10:00 Securing Hardware 00:11:00 Securing Endpoints 00:09:00 Exam Question Review 00:02:00 Linux Software RAID Lab 00:08:00 Ask Me Anything (AMA) 00:02:00 Section 07: The Basic LAN The OSI Model 00:13:00 ARP Cache Poisoning 00:09:00 Other Layer 2 Attacks 00:05:00 Network Planning 00:07:00 Load Balancing 00:06:00 Securing Network Access 00:06:00 Honeypots 00:06:00 Firewalls 00:08:00 Proxy Servers 00:06:00 Network and Port Address Translation 00:07:00 IP Security (IPsec) 00:09:00 Virtual Private Networks (VPNs) 00:10:00 Intrusion Detection and Prevention Systems (IDS/IPS) 00:13:00 Exam Question Review 00:03:00 Linux Snort IDS Lab 00:07:00 Ask Me Anything (AMA) 00:01:00 Section 08: Securing Wireless LANs Wi-Fi Encryption Standards 00:10:00 RFID, NFC, and Bluetooth 00:07:00 Wi-Fi Coverage and Performance 00:08:00 Wi-Fi Discovery and Attacks 00:12:00 Cracking WPA2 00:10:00 Wi-Fi Hardening 00:11:00 Exam Question Review 00:02:00 WPA2 Cracking Lab 00:06:00 Ask Me Anything (AMA) 00:01:00 Section 09: Securing Public Servers Defining a Public Server 00:01:00 Common Attacks and Mitigations 00:10:00 Containers and Software-Defined Networking 00:11:00 Hypervisors and Virtual Machines 00:08:00 Cloud Deployment Models 00:09:00 Cloud Service Models 00:08:00 Securing the Cloud 00:10:00 Exam Question Review 00:02:00 Docker Container Lab 00:04:00 Ask Me Anything (AMA) 00:02:00 Section 10: Securing Dedicated Systems Embedded Systems 00:13:00 Industrial Control System (ICS) 00:07:00 Internet of Things (IoT) Devices 00:10:00 Connecting to Dedicated and Mobile Systems 00:11:00 Security Constraints for Dedicated Systems 00:05:00 Mobile Device Deployment and Hardening 00:11:00 Exam Question Review 00:03:00 Smartphone Hardening Lab 00:03:00 Ask Me Anything (AMA) 00:02:00 Section 11: Physical Security Physical Security Overview 00:01:00 Physical Security 00:10:00 Keylogger Demo 00:05:00 Environmental Controls 00:05:00 Exam Question Review 00:02:00 Physical Security Lab 00:03:00 Ask Me Anything (AMA) 00:03:00 Section 12: Secure Protocols and Applications DNS Security 00:05:00 FTP Packet Capture 00:03:00 Secure Web and E-mail 00:12:00 Request Forgery Attacks 00:05:00 Cross-Site Scripting Attacks 00:07:00 Web Application Security 00:08:00 Web App Vulnerability Scanning 00:06:00 Exam Question Review 00:03:00 OWASP ZAP Web App Scan Lab 00:04:00 Ask Me Anything (AMA) 00:02:00 Section 13: Testing Infrastructure Testing Infrastructure Overview 00:05:00 Social Engineering 00:06:00 Social Engineering Attacks 00:11:00 Vulnerability Assessments 00:09:00 Penetration Testing 00:10:00 Security Assessment Tools 00:12:00 The Metasploit Framework 00:08:00 Exam Question Review 00:02:00 Hping3 Forged Packet Lab 00:06:00 Ask Me Anything (AMA) 00:02:00 Section 14: Dealing with Incidents Incident Response Overview 00:03:00 Incident Response Plans (IRPs) 00:06:00 Threat Analysis and Mitigating Actions 00:08:00 Digital Forensics 00:10:00 Gathering Digital Evidence 00:10:00 Business Continuity and Alternate Sites 00:06:00 Data Backup 00:10:00 Exam Question Review 00:01:00 Autopsy Forensic Browser Lab 00:05:00 Ask Me Anything (AMA) 00:02:00 Assignment Assignment - CompTIA Security+ 00:00:00