502 Ecosystem courses

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.

Venturing into the startup landscape and seeking the right pitch to leave an impact? The 'Advanced Pitching for Startups' course unfolds the art and science behind crafting an impeccable pitch. Navigate through sections that elucidate how to enchant investors with your vision, tackle unprecedented challenges, and portray your solution in an engaging manner. As you journey further, the course empowers you to pose questions with astuteness and navigate through any Q&A with unwavering confidence. Lastly, personalise your pitch with project-specific insights, ensuring your startup story remains unforgettable. Learning Outcomes Understand the art of storytelling in pitches to captivate potential investors. Develop strategies to address and overcome complex challenges faced by startups. Master the skill of unveiling solutions that resonate with the target audience. Cultivate the ability to pose astute and thought-provoking questions. Enhance competence in handling Q&A sessions effectively. Why buy this Advanced Pitching for Startups course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Advanced Pitching for Startups 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 Advanced Pitching for Startups course for? Aspiring entrepreneurs preparing to launch their startups. Startup founders seeking to refine their pitching technique. Business students eager to delve into the startup ecosystem. Investors looking to understand the nuances of a compelling pitch. Mentors and coaches aiming to guide startups more effectively. Prerequisites This Advanced Pitching for Startups does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Pitching for Startups 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 Startup Founder: £25,000 - £100,000+ (varying greatly depending on the startup's success) Investment Analyst: £40,000 - £70,000 Business Consultant: £30,000 - £60,000 Venture Capitalist: £60,000 - £120,000+ Pitching Coach: £35,000 - £65,000 Business Development Manager: £35,000 - £55,000 Course Curriculum COURSE INTRO GET READY 00:02:00 Section I - SELLING THE DREAM SECTION INTRO: THE DREAM 00:01:00 SLIDE 01: HERO IMAGE 00:04:00 SLIDE 02: HIGH-LEVEL CONCEPT 00:03:00 SLIDE 03: TEAM 00:02:00 SECTION OUTRO: PITCH FLOW 00:01:00 Section II - SOLVING THE UNSOLVABLE SECTION INTRO: THE REALITY 00:01:00 SLIDE 04: STATE OF THE ART 00:01:00 SLIDE 05: MARKET ANALYSIS 00:03:00 SLIDE 06: YOUR IMPACT 00:01:00 SECTION OUTRO: PITCH FLOW 00:01:00 Section III - REVEALING THE SOLUTION SECTION INTRO: THE REVEAL 00:01:00 SLIDE 07: CORE FEATURES 00:02:00 SLIDE 08: ECOSYSTEM 00:01:00 SLIDE 09: TRACTION 00:03:00 SLIDE 10: MARKET FIT 00:02:00 SLIDE 11: ADVANTAGES 00:01:00 SLIDE 12: MILESTONES 00:01:00 SECTION OUTRO: PITCH FLOW 00:01:00 Section IV - ASKING WITH INTELLECT SECTION INTRO: THE ASK 00:01:00 SLIDE 13: REVENUE MODEL 00:02:00 SLIDE 14: FINANCIAL PROJECTIONS 00:02:00 SLIDE 15: THE ASK 00:02:00 SECTION OUTRO: PITCH FLOW 00:01:00 Section V - BULLET PROOF Q&A SECTION INTRO: THE SMOOTH END 00:01:00 SLIDE 16: CLOSING SLIDE 00:02:00 SLIDE 17: RISK REGISTRY 00:01:00 SECTION OUTRO: PITCH FLOW 00:01:00 Section VI - PROJECT SPECIFIC SLIDES SECTION INTRO 00:01:00 OPTIONAL SLIDE: AWARDS 00:01:00 OPTIONAL SLIDE: BOARD & ADVISORS 00:01:00 OPTIONAL SLIDE: EXIT STRATEGY 00:01:00 COURSE OUTRO GOOD LUCK! 00:01:00 Assignment Assignment - Advanced Pitching for Startups 00:00:00

2 QLS Endorsed Courses | CPD Certified | Free PDF & QLS Hardcopy Certificates | 180 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

🚀 Unlock Your Profit Potential with 'Maximizing Profits Using Thrivecart' Online Course! 🚀 Are you ready to transform your business and skyrocket your profits? Introducing our groundbreaking online course: 'Maximizing Profits Using Thrivecart' - the ultimate guide to supercharging your revenue with the power of the leading e-commerce platform!   🌟 Why Thrivecart? Thrivecart isn't just another online shopping cart - it's a game-changer for entrepreneurs and business owners looking to take their profits to new heights. With its user-friendly interface and robust features, Thrivecart empowers you to streamline your sales process, increase conversions, and maximize your bottom line.   🚀 What You'll Learn: Mastering the Thrivecart Dashboard: Navigate through Thrivecart like a pro and unlock its full potential to optimize your sales process. Advanced Product Setup: Learn the insider secrets to create irresistible offers that compel your customers to take action and boost your average transaction value. Automated Sales Funnels: Discover how to set up automated sales funnels that work around the clock, turning leads into loyal customers while you focus on growing your business. Conversion-Boosting Strategies: Implement proven strategies to increase your conversion rates, reduce cart abandonment, and turn more visitors into paying customers. Integration Mastery: Seamlessly integrate Thrivecart with other tools and platforms to create a cohesive and efficient business ecosystem. Optimizing for Profits: Uncover the tactics to optimize your pricing, upsells, and cross-sells for maximum profitability without sacrificing customer satisfaction. Analytics and Data Insights: Leverage the power of data to make informed decisions, refine your strategies, and continuously improve your business performance.   💡 Why Choose This Course? ✅ Expert Guidance: Learn from industry experts with a proven track record of success in maximizing profits using Thrivecart. ✅ Actionable Insights: Receive step-by-step guidance and actionable tips that you can implement immediately for tangible results. ✅ Community Support: Join a thriving community of like-minded entrepreneurs, share experiences, and get support on your journey to success. ✅ Lifetime Access: Gain lifetime access to the course material, ensuring you stay ahead of the curve with future updates and advancements.   💰 Don't Miss Out on This Limited-Time Opportunity! Ready to revolutionize your business and start maximizing your profits with Thrivecart? Enroll now and take the first step toward a more profitable and sustainable future! Act fast - success favors the bold. Course Curriculum

🚀 Unleash Your Potential with the Information Enterprise Launchpad Course! 🚀 Are you ready to soar to new heights in the digital landscape? Introducing the Information Enterprise Launchpad, your ultimate guide to transforming information into success! 🌐   In today's fast-paced world, information is power. Imagine having the skills and knowledge to harness that power and turn it into a thriving enterprise. Whether you're a seasoned entrepreneur or a budding business enthusiast, this course is designed to propel you forward.   Key Features: Strategic Information Management: Learn to sift through the digital noise and extract valuable insights that can shape your business strategy. We'll guide you through the art of data analysis and interpretation. Innovative Business Models: Discover cutting-edge business models that leverage information as a core asset. From data monetization to creating a digital ecosystem, we'll explore diverse approaches that fit your unique vision. Digital Marketing Mastery: Gain a competitive edge in the digital landscape with our in-depth digital marketing modules. Learn to optimize your online presence, create compelling content, and engage with your audience effectively. Technology Integration: Stay ahead of the curve by understanding how to integrate the latest technologies into your enterprise. From AI and machine learning to blockchain, we'll demystify complex concepts and show you practical applications. Entrepreneurial Mindset Development: Cultivate the mindset of a successful entrepreneur. Overcome challenges, embrace innovation, and develop resilience in the face of uncertainty. Expert-Led Sessions: Benefit from insights shared by industry experts and successful entrepreneurs who have mastered the art of leveraging information for business growth.   What You'll Gain: ✅ Actionable Strategies: Walk away with actionable strategies that you can implement immediately to enhance your business. ✅ Networking Opportunities: Connect with like-minded individuals and industry experts through our exclusive community forums and networking events. ✅ Lifetime Access: Enjoy lifetime access to course materials and updates, ensuring that you stay at the forefront of the ever-evolving digital landscape. ✅ Certificate of Completion: Receive a prestigious certificate upon successfully completing the course, showcasing your expertise in information enterprise.   Don't miss your chance to revolutionize your approach to business in the digital age. The Information Enterprise Launchpad is your ticket to success!   🔥 Enroll now and embark on a journey to transform information into enterprise excellence! 🔥 Course Curriculum

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost

Overview This comprehensive course on Environment Management will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Environment Management 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 Environment Management. It is available to all students, of all academic backgrounds. Requirements Our Environment Management is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 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 1 sections • 10 lectures • 04:13:00 total length •Module 01: Environment and Ecology: 00:20:00 •Module 02: Environmental Issues: 00:26:00 •Module 03: Environmental Planning: 00:21:00 •Module 04: Environmental Management System: 00:31:00 •Module 05: Ecosystem Management: 00:28:00 •Module 06: Environmental Law and Policy: 00:23:00 •Module 07: Improving Environmental Performance: 00:24:00 •Module 08: Environmental Management Audit: 00:37:00 •Module 09: Situational Environmental Management: 00:26:00 •Module 10: Review and Performance: 00:17:00

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost