488 Ecosystem courses delivered Online

Level 3 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access

Level 3 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access

Level 3 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access

Level 4 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access

Level 4 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access

Overview This comprehensive course on Animal Behaviour and Psychology will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Animal Behaviour and Psychology comes with accredited certification which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. ** Completing this course does not imply that you are qualified to work as a Practitioner Psychologist. If you are seeking a course that fits the HCPC's standards, please contact the HCPC or the RCSLT. ** 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 Animal Behaviour and Psychology. It is available to all students, of all academic backgrounds. Requirements Our Animal Behaviour and Psychology 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 5 sections • 5 lectures • 02:40:00 total length •Introduction to Animal Care: 00:24:00 •Basic Animal Health: 00:22:00 •Evolution and Ecosystem: 00:33:00 •Animal Behaviour: 00:47:00 •Animal Psychology: 00:34:00

Overview This comprehensive course on Forestry will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Forestry comes with accredited certification which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. 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 Forestry. It is available to all students, of all academic backgrounds. Requirements Our Forestry 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 10 sections • 10 lectures • 03:06:00 total length •Introduction to Forestry: 00:24:00 •Forest Soil: 00:22:00 •Forest Menstruation: 00:22:00 •Forest Surveying: 00:21:00 •Silviculture: 00:22:00 •Forest Ecosystem: 00:24:00 •Timber Harvesting (Part One): 00:16:00 •Timber Harvesting (Part Two): 00:13:00 •Urban Forestry: 00:22:00 •Assignment - Forestry: 00:00:00

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.

Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.

Fall into Savings. Enjoy the biggest price fall this Autumn! Tired of browsing and searching for a Sustainability and Environmental Conservation course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this extensive bundle that has everything you need to succeed. After surveying thousands of learners just like you and considering their valuable feedback, this all-in-one Sustainability and Environmental Conservation bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand Sustainability and Environmental Conservation course that will enhance your skills and prepare you for the competitive job market. Also, our experts are available for answering your queries on Sustainability and Environmental Conservation and help you along your learning journey. Advanced audio-visual learning modules of these Sustainability and Environmental Conservation courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once. Furthermore, to help you showcase your expertise in Sustainability and Environmental Conservation, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest. This Sustainability and Environmental Conservation Bundle Consists of the following Premium courses: Course 01: Sustainable Energy and Development Diploma Course 02: Conservation Diploma Course Course 03: Carbon Literacy Knowledge | Course Course 04: Environmental Law Course 05: Sustainable Living Course 06: Solving Climate Change Problems with Renewable Energy Course 07: Environmental Health Course 08: Process Improvement: Reduce Waste Course 09: Environment Management Course 10: Solar Energy Course 11: LEED Green Associate Course 12: Land Management Course Course 13: Health And Wellness Diploma Course 14: Creative Thinking for Everyday Life Enrol now in Sustainability and Environmental Conservation to advance your career, and use the premium study materials from Apex Learning. How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (For The Title Course) Hard Copy Certificate: Free (For The Title Course) The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Sustainability and Environmental Conservation expertise and essential knowledge, which will assist you in reaching your goal. Curriculum of Bundle Course 01: Sustainable Energy and Development Diploma Module 01: An Introduction to Sustainable Energy Module 02: Solar Energy: Thermal Module 03: Solar Energy: Photovoltaics Module 04: Wind Energy Module 05: Bioenergy Module 06: Geothermal Energy Module 07: Tidal Energy Module 08: Environmental Impacts: A Global and Regional Assessment Module 09: Renewable Energy and Sustainable Development Module 10: The Future of Renewable Energy in the UK into the 2020s and Beyond Course 02: Conservation Diploma Course Module 01: The Fundamentals of Conservation Module 02: Introduction to Biodiversity Module 03: Introduction to Ecosystem Module 04: Species and Ecosystems Module 05: Wildlife Conservation Module 06: Ocean Challenges and Solutions Module 07: Conservation Project Planning Course 03: Carbon Literacy Knowledge | Course Module 01: Introduction to Carbon Literacy Module 02: The Carbon Cycle Module 03: Global Warming and Climate Change Module 04: Solutions for Global Warming Module 05: Steps to Take for a Cleaner Tomorrow Course 04: Environmental Law Module 01: Legal System Module 02: What is Environmental Law Module 03: International Environment law Module 04: Environmental Organisations Module 05: National Environmental Legacy Act Module 06: The Environment and Economics Part 1 Module 07: The Environment and Economics Part 2 Module 08: Climate Change Module 09: Environmental Impact Assessment Module 10: Nature Conservation Module 11: Kyoto Protocol and Paris Agreement Module 12: Sustainable Development Module 13: Compliance and Governance of Law Module 14: Right to Information, Participation and Justice Module 15: Enforcement of Environmental Law Course 05: Sustainable Living Module 01: An Overview of Sustainable Living Module 02: Sustainable Food Module 03: Water Preservation Module 04: Wastewater Recycling Module 05: Conserving Energy Module 06: What is Bioremediation? Module 07: How to Live Green Course 06: Solving Climate Change Problems with Renewable Energy Renewable Energy Basics Renewable Energy Applications Course 07: Environmental Health Module 01: Intro to Environmental Health Module 02: Waste, Pollution and Pollutants Module 03: Environment, Pollution, Climate Change and Health Module 04: Recovering Resources and Managing Waste Module 05: Food Waste Module 06: Plastic Module 07: Air Pollution Module 08: Water Module 09: Environmental Sustainability Course 08: Process Improvement: Reduce Waste Section 01: Introduction Section 02: Fundamentals of Waste Section 03: The 8 Wastes Section 04: VA vs. NVA Section 05: Process Mapping Tools Section 06: Case Study Section 07: Close Out Course 09: Environment Management Module 01: Environment and Ecology Module 02: Environmental Issues Module 03: Environmental Planning Module 04: Environmental Management System Module 05: Ecosystem Management Module 06: Environmental Law and Policy Module 07: Improving Environmental Performance Module 08: Environmental Management Audit Module 09: Situational Environmental Management Module 10: Review and Performance Course 10: Solar Energy Unit 01: Basics of Solar Energy System Unit 02: Batteries in PV System Unit 03: Components and Design of Off Grid Solar Energy System Unit 04: Designing of ON Grid Solar Energy System Unit 05: Design of PV System Using PVSyst Programme Unit 06: Solar Water Pumping System Unit 07: Protection of PV System Unit 08: Design Using Excel Sheet Unit 09: Single Line Diagram of PV System Unit 10: MATLAB and ETAP PV Simulation Course 11: LEED Green Associate Module 01: Introduction to LEED Green Associate Module 02: Integrative Process Module 03: Location & Transportation Module 04: Sustainable Sites Module 05: Water Efficiency Module 06: Energy & Atmosphere Module 07: Materials & Resources Module 08: Indoor Environment Quality Module 09: Innovation Module 10: Regional Priority Module 11: Completion Course 12: Land Management Course Module 01: Land Management: An Introduction Module 02: Land Use and Land Use Planning Module 03: Soil Management Module 04: Land Degradation and Management Module 05: Weed Management Module 06: Watershed Management Module 07: Irrigation Management Module 08: Land Tenure, Administration and Transection Module 09: Land Registration and Acquisition Module 10: Land Law Course 13: Health And Wellness Diploma Health And Wellness Diploma Introduction Diet Fundamentals Food Groups Explained Different Diets Explained Diet Coaching Weight Loss & Muscle Growth Coaching Exercise Coaching: Cardio Exercise Coaching: Resistance Training Exercise Coaching: Flexibility Wellness & Mental Coaching Bonus: Coaching Tools Course 14: Creative Thinking for Everyday Life Module 01: Course Structure Module 02: Introduction Module 03: Mind Tuning Module 04: Techniques I Module 05: Techniques II Module 06: Techniques III Module 07: Conclusion CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Sustainability and Environmental Conservation bundle. Requirements Our Sustainability and Environmental Conservation course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. Career path Having this Sustainability and Environmental Conservation expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included You will get the PDF Certificate for the title course (Sustainable Energy and Development Diploma) absolutely Free! Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Sustainable Energy and Development Diploma) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.