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If you are working on data science projects and want to create powerful visualization and insights as an outcome of your projects or are working on machine learning projects and want to find patterns and insights from your data on your way to building models, then this course is for you. This course exclusively focuses on explaining how to build fantastic visualizations using Python. It covers more than 20 types of visualizations using the most popular Python visualization libraries, such as Matplotlib, Seaborn, and Bokeh along with data analytics that leads to building these visualizations so that the learners understand the flow of analysis to insights.

Overview Ensure you have all the knowledge and facts needed to craft a safe and effective fitness plan for your personal goals. This intuitive course will raise your awareness of the need for nutrition and exercise in a lifestyle and drive you to a healthier state. The Improving Personal Health and Nutrition Level 3 course understands that people need help and guidance to get truly fit and healthy, so you will be taught the many different aspects you need to consider when striving for your goals. Alongside dietary changes and exercise routines, you will be advised on your personal anatomy and also your psychological requirements. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this Improving Personal Health and Nutrition Level 3. It is available to all students, of all academic backgrounds. Requirements Our Improving Personal Health and Nutrition Level 3 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 11 sections • 76 lectures • 03:01:00 total length •Course Promo: 00:02:00 •Introduciton & What you will learn in the course: 00:04:00 •who this course is for: 00:02:00 •what is nutrition: 00:01:00 •The principles of healthy dieting: 00:04:00 •the true dieting pyramid: 00:04:00 •Calories Explained: 00:04:00 •bodyweight and health: 00:05:00 •Calories & bodyweight in a healthy diet: 00:02:00 •the twinkie diet: 00:02:00 •weight loss and health: 00:03:00 •How many calories do you need daily: 00:02:00 •How To Determin Your Optimal Calorie Intake: 00:03:00 •healthy weight ranges: 00:02:00 •How to lose weight if you are close to the optimal range: 00:03:00 •How to lose weight when you start from a higher weight: 00:02:00 •Diet breaks: 00:05:00 •How to track calories: 00:05:00 •How to lose weight without tracking calories: 00:04:00 •food composition intro: 00:03:00 •Protein Composition copy: 00:02:00 •Carbohydrate Composition copy: 00:03:00 •Fat Composition copy: 00:01:00 •Overview food composition: 00:03:00 •Macros intro: 00:01:00 •Protein Explained: 00:02:00 •protein needs for overall health: 00:02:00 •How Much Carbs should you eat per day copy: 00:01:00 •How Much Fat Should You Eat Per Day copy: 00:04:00 •Overview Macronutrients: 00:03:00 •Nutrient Timing Intro: 00:02:00 •Nutrient Timing Facts: 00:04:00 •Nutrient Timing Recommendations: 00:02:00 •Supplements intro: 00:04:00 •Why Mulitvitamins arent a good idea: 00:02:00 •supplements for vegans and vegetarians: 00:02:00 •supplements for joint health: 00:02:00 •supplements for improved sleep: 00:02:00 •supplements for better memory and focus: 00:02:00 •Supplements Overview: 00:01:00 •How to naturally increase testosterone: 00:07:00 •basics of healthy dieting: 00:02:00 •making changs towards a healthier diet: 00:04:00 •How to read a nutrition label copy: 00:03:00 •diet myths into: 00:01:00 •Dieting myth #1 Carbs are bad for you copy: 00:02:00 •Dieting Myth #2 Fat is bad for you copy: 00:02:00 •Dieting Myth #3 Protein is bad for you copy: 00:04:00 •Dieting Myth #4 Eating Eggs Raises Cllesterol copy: 00:01:00 •Dieting Myth #5 Avoid Salt At All Cost copy: 00:01:00 •Dieting Myth #6 Eat several small meals throughout the day to lose weight copy: 00:01:00 •Dieting Myth #7 Diet Foods Will Lead To Weight Loss copy: 00:01:00 •Red meat always causes cancer copy: 00:03:00 •Common Diets Intro 2 copy: 00:01:00 •Gluten Free Diet Explained copy: 00:03:00 •Paleo Diet Explained copy: 00:04:00 •Low Carb Diet Explained copy: 00:03:00 •Intermittend Fasting Explained copy: 00:03:00 •Vegan Diet Explained copy: 00:05:00 •Micronutrients Introduction 2 copy: 00:01:00 •Vitamin A copy: 00:02:00 •Vitamin B copy: 00:01:00 •Vitamin C copy: 00:01:00 •Vitamin D copy: 00:02:00 •Vitmain E copy: 00:01:00 •Vitamin K copy: 00:01:00 •Calcium copy: 00:02:00 •Magnesium copy: 00:01:00 •Phosphorus copy: 00:01:00 •Potassium copy: 00:01:00 •Sodium copy: 00:01:00 •Copper copy: 00:01:00 •Iron copy: 00:01:00 •Zinc copy**: 00:02:00 •water copy: 00:04:00 •Assignment - Improving Personal Health and Nutrition Level 3: 00:00:00

Embark on a captivating journey through the art of digital photography with our Adobe Lightroom CC Course. This course isn't just a guide; it's an immersive experience designed to elevate your photography to new heights. Whether you're a novice or a seasoned photographer, our meticulously crafted curriculum in Lightroom Classic CC and Lightroom CC will unravel the secrets of professional photo editing. Delve into the intricacies of Lightroom Classic CC, where you'll master everything from basic edits like cropping and rotating to advanced techniques such as split toning and range masks. Transition seamlessly to Lightroom CC, exploring its intuitive features for web-based photo editing. Our course isn't just about sliders and adjustments; it's about transforming your photos into visual masterpieces that tell compelling stories. Learning Outcomes Navigate the Lightroom Classic CC and Lightroom CC interfaces with confidence. Master essential photo editing techniques, from exposure adjustments to lens corrections. Explore advanced features like graduated and radial adjustments for creative editing. Understand the nuances of portrait editing and night photo enhancement. Export and share your edited photos seamlessly across platforms. Why choose this Adobe Lightroom CC course? 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. Who is this Adobe Lightroom CC course for? Photography enthusiasts eager to enhance their editing skills. Beginners looking to navigate the world of photo post-processing. Content creators and social media influencers seeking visually stunning images. Professionals wanting to streamline their photo editing workflow. Anyone with a passion for transforming ordinary photos into extraordinary visual narratives. Career path Freelance Photo Editor: £20,000 - £35,000 Social Media Content Creator: £25,000 - £40,000 Photography Educator: £28,000 - £45,000 Digital Marketing Specialist: £30,000 - £50,000 E-commerce Product Photographer: £22,000 - £38,000 Wedding and Events Photographer: £26,000 - £42,000 Prerequisites This Adobe Lightroom CC does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Adobe Lightroom CC 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. Course Curriculum Lightroom Classic CC Intro to Lightroom Classic CC 00:05:00 Importing and Organizing in Lightroom Classic CC 00:11:00 Crop and Rotate Lightroom Classic CC 00:05:00 White Balance in Lightroom Classic 00:08:00 Exposure in Lightroom Classic CC 00:06:00 Color and Saturation in Lightroom Classic CC 00:09:00 Sharpening and Noise Reduction in Lightroom Classic CC 00:07:00 Vignettes, Grain and Dehaze in Lightroom Classic CC 00:06:00 Exporting in Lightroom Classic CC 00:10:00 Lens Corrections in Lightroom Classic CC 00:05:00 Split Tone in Lightroom Classic CC 00:05:00 Removing Blemishes With the Heal and Clone Tools in Lightroom Classic CC 00:08:00 Graduated, Radial and Brush Adjustments in Lightroom Classic CC 00:10:00 Adjustment Brush Presets in Lightroom Classic CC 00:03:00 Range Masks in Lightroom Classic CC 00:05:00 Full Edit - Portrait in Lightroom Classic CC 00:19:00 Lightroom CC Intro to Lightroom CC 00:03:00 Import and Organize in Lightroom CC 00:10:00 Crop and Rotate in Lightroom CC 00:03:00 White Balance and Saturation in Lightroom CC 00:06:00 Light - Exposure and Tone Curve in Lightroom CC 00:08:00 Color Mixer in Lightroom CC 00:02:00 Effects in Lightroom CC 00:05:00 Split Toning in Lightroom CC 00:01:00 Details in Lightroom CC 00:05:00 Optics in Lightroom CC 00:03:00 Geometry in Lightroom CC 00:04:00 Exporting and Sharing Lightroom CC 00:02:00 Healing and Clone Brushes in Lightroom CC 00:04:00 Brush Adjustments Lightroom CC 00:04:00 Radial and Linear Gradients Lightroom CC 00:05:00 Advanced Optione and Presets in Lightroom CC 00:04:00 Full Edit - Night Photo in Lightroom CC 00:11:00 Full Edit - Portrait in Lightroom CC 00:14:00 Editing Photos in Your Web Browses With Lightroom CC 00:03:00

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills 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. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. 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.

Explore offline-first app development with Angular, Ionic, PouchDB, and CouchDB. Sync data effortlessly, design for web and mobile, and deploy with ease for a seamless user experience. Learn data synchronization, advanced features such as RxJS and custom pipes, implement state machines with XState, and build scalable, multi-platform web apps.

Phlebotomy and venipuncture is a rewarding career in healthcare with good job prospects. The average salary for a phlebotomist in the UK is £23,650 per year, and the job outlook is expected to grow by 17% by 2030. Phlebotomists can work in a variety of settings, including hospitals, clinics, and blood donation centres. They are responsible for collecting blood samples for diagnostic tests, so it is a job that requires attention to detail and compassion for patients. If you are looking for a rewarding career in healthcare, phlebotomy and venipuncture is a great option. With the right skillsets, you can take your first step towards a stable and well-paying job in this growing field. Our Phlebotomy & Venipuncture course starts with the basics of Phlebotomy & Venipuncture and gradually progresses towards advanced topics. Therefore, each lesson of this Phlebotomy & Venipuncture course is intuitive and easy to understand. 6 CPD Accredited Courses Are: Course 01: Phlebotomy Course 02: Venepuncture Level 3 Course 03: Sterile Compounding Preparations Course 04: Control and Administration of Medicines Course 05: Pharmacy Technician & Assistant Course 06: Infection Control & Precautions Why would you choose the Phlebotomy & Venipuncture course: Lifetime access to Phlebotomy & Venipuncture course materials Full tutor support is available from Monday to Friday with the Phlebotomy & Venipuncture course Learn Phlebotomy & Venipuncture skills at your own pace from the comfort of your home Gain a complete understanding of the Phlebotomy & Venipuncture course Accessible, informative Phlebotomy & Venipuncture learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Phlebotomy & Venipuncture Study Phlebotomy & Venipuncture in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Phlebotomy & Venipuncture course Course 01: Phlebotomy: This course provides comprehensive training in Phlebotomy, covering venepuncture techniques, anatomy, pre- and post-procedure protocols, and blood donation procedures. Curriculum Breakdown Module 01: Venepuncture: A Method of Phlebotomy Module 02: Anatomy and Physiology Module 03: Before Venepuncture Module 04: During Venepuncture Module 05: After Venepuncture Module 06: Venepuncture for Blood Donation Module 07: Glossary Module 08: Appendix of phlebotomy Course 02: Venepuncture Level 3: Advance your Phlebotomy skills with in-depth knowledge of blood circulation, phlebotomy equipment, routine and special blood collection procedures, and infection control. Curriculum Breakdown Module 01: Blood Circulation, Function, and Composition Module 02: Phlebotomy Equipment Module 03: Routine Venipuncture Module 04: Venipuncture Complications and Pre-Examination Variables Module 05: Special Blood Collection Procedure Module 06: Infection Control and Risk Management Course 03: Sterile Compounding Preparations: Master the principles of Phlebotomy in sterile compounding, including precautions, laminar airflow hood usage, and pharmaceutical demonstrations. Curriculum Breakdown Module 01: Introduction Module 02: Universal Precautions Module 03: The Laminar Air Flow Hood (LAF) 3 lectures Module 04: Sterile Compounding Pharmaceuticals Demonstrations Module 05: Compounding Pharmacy Math Module 06: BONUS Module 07: REVIEW OF THE STERILE COMPOUNDING PROCESS Course 04: Control and Administration of Medicines: Learn Phlebotomy essentials for effective medicine management, prescribing, and optimizing medication use. Curriculum Breakdown Module 01: Medicine Management Fundamentals Module 02: Importance of Medicine Management Module 03: Prescribing Medication Effectively Module 04: Common Problems - Pharmacological Management Module 05: Common Medicines to Use Module 06: Palliative Care Module 07: The Four Principles of Medicine Optimisation Module 08: Managing Medication in Residential Aged Care Facilities Module 09: Law and Legislation Course 05: Pharmacy Technician & Assistant: Develop skills in Phlebotomy, patient counselling, and safe dispensing practices for pharmacy technicians and assistants. Curriculum Breakdown Module 1: Introduction to Pharmacy Assistant and Pharmacy Technician Module 2: Job Role of Pharmacy Technicians Module 3: Pharmacy Assistant Patient Counselling Guide Module 4: Communication in Pharmacy Settings Module 5: The Pharmacy Team and Practices Module 6: Prescription and Dispensing in Pharmacies Module 7: Dispensing Methods, EPS, Minimising Dispensing Errors in Pharmacies Module 8: Inventory Control and Management in Pharmacies Module 9: Standard Operating Procedures (SOPs) Module 10: Health and Safety Risks Assessment and Pharmaceutical Terminology Course 06: Infection Control & Precautions: Understand Phlebotomy's role in infection prevention, control policies, and immunization strategies in healthcare settings. Curriculum Breakdown Module 01: Infection Prevention and Control Policy in the UK Module 02: Principles of Prevention and Control of Infection Module 03: Immunization Module 04: Infections Spread by Food and Water Module 05: Infections Spread by Animals and Insects and Less Common Infections Found in the UK Module 06: Infections & Diseases Spread by Person-to-Person Contact Module 07: Infections Spread by Sexual Contact Module 08: Infections Spread by Blood and Body Fluids CPD 60 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Phlebotomy & Venipuncture course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Phlebotomy & Venipuncture. It is also great for professionals who are already working in Phlebotomy & Venipuncture and want to get promoted at work. Requirements To enrol in this Phlebotomy & Venipuncture course, all you need is a basic understanding of the English Language and an internet connection. Career path The Phlebotomy & Venipuncture course will enhance your knowledge and improve your confidence. Phlebotomy Technician Medical Laboratory Assistant Clinical Support Worker Healthcare Assistant Phlebotomy Supervisor/Team Lead Certificates CPD Accredited PDF Certificate Digital certificate - Included 6 CPD Accredited PDF Certificate

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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 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. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 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. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

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A 100% learning satisfaction guarantee with your Forex Trading & Technical Analysis Course Curriculum Breakdown of the Forex Trading & Technical Analysis Course 01: Forex Trading Introduction to Forex Trading Major Currencies and Market Structure Kinds of Foreign Exchange Market Money Management Fundamental Analysis Technical Analysis Pitfalls and Risks Managing Risk Trading Psychology Course 02: Stock Market Investing for Beginners Module 01: Introduction to the Course Module 02: Introduction to Stocks Module 03: Money Required for Primary Investment Module 04: Opening an Investment Account Module 05: Brokerage Account Walkthrough Module 06: Finding Winning Stocks Module 07: Earning from Dividends Module 08: Diversifying Portfolio Module 09: Investment Plan Module 10: Rebalancing Portfolio Module 11: Understanding Order Types Module 12: Investment Tax Module 13: Investment Rules: Rule-1 Module 14: Investment Rules: Rule-2 Module 15: Investment Rules: Rule-3 Module 16: Investment Rules: Rule-4 Module 17: Investment Rules: Rule-5 Module 18: Stock Market Dictionary Module 19: Setting Up the Trading Platform Course 03: Passive Income - An Ultimate Guide Module 01: Introduction Preview Of Course Module 02: Passive Income Masterclass Build Financial Security What Are Recurring Income Streams What is Residual Income Types of Recurring Income Types of Residual Income Relationship Between Recurring, Residual. and Passive Income Building Wealth Strategies Module 03: Relationship Between Recurring, Residual. and Passive Income How They're Similar and also Different What is Passive Income and Its Relationship to Passive and Residual Income Examples of Passive Income The Truth About Active Income vs Passive Income Active Income Becomes Passive Income Module 04: Types of Recurring Income Hard contracts Auto-renewal subscriptions Build a Membership Program for Your Business Become an Affiliate for Other Companies Products Combine Online Membership and Physical Product Delivery Module 05: Types of Residual Income Consider Investing Write a Book or E-Book Build an Online Course Create an App Launch a Podcast Module 06: What Are Recurring Income Streams What Is the Recurring Revenue Model? 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