2300 Intelligence courses in Cardiff delivered On Demand

48-Hour Knowledge Knockdown! Prices Reduced Like Never Before! Have you ever looked at a map and wondered how it was created? Have you ever wanted to gain the skills to analyse spatial data? Look no further than our Spatial Analysis in ArcGIS bundle. With our QLS-endorsed Spatial Analysis in ArcGIS course, you'll gain a deep understanding of geographic information systems and how to utilise ArcGIS software for spatial data analysis. Plus, receive a free QLS hardcopy certificate upon completion, an essential addition to your credentials. But the learning doesn't stop there. Our bundle includes ten more relevant courses, all CPD-QS accredited. From ArcGIS for Hydrology to Web Scraping and Mapping Dam Levels in Python and Leaflet, you'll gain a comprehensive skill set in the field of spatial analysis. Don't just take our word for it. Our courses have been meticulously designed by experienced people to provide you with a theoretical understanding of the subject matter. And with our user-friendly platform, you can learn at your own pace and convenience. Unlock the power of spatial analysis with our bundle today. Enrol now and start your journey towards becoming a skilled spatial analyst. This Spatial Analysis in ArcGIS Bundle Package includes: Course 01: Award in Spatial Analysis in ArcGIS at QLS Level 2 10 Premium Additional CPD QS Accredited Courses - Course 01: ArcGIS for Hydrology Course 02: Remote Sensing in ArcGIS Course 03: QGIS Cartography Course 04: Business Intelligence and Data Mining Diploma Course 05: Python Data Science Course 06: Spatial Data Visualization and Machine Learning in Python Level 4 Course 07: Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4 Course 08: Learn to Use Python for Spatial Analysis in ArcGIS Course 09: Maps in R Shiny and Leaflet Course 10: The Basics of ArcGIS for Hydrology Why Prefer This Spatial Analysis in ArcGIS Bundle? You will receive a completely free certificate from the Quality Licence Scheme Option to purchase 10 additional certificates accredited by CPD Get a free Student ID Card - (£10 postal charges will be applicable for international delivery) Free assessments and immediate success results 24/7 Tutor Support After taking this Spatial Analysis in ArcGIS bundle courses, you will be able to learn: Develop a comprehensive understanding of spatial analysis and its applications in the industry. Gain practical experience using ArcGIS software for spatial data analysis and hydrology. Learn to use remote sensing techniques in ArcGIS for data collection and analysis. Master the art of cartography using QGIS software. Gain expertise in business intelligence, data mining, and data science using Python. Explore spatial data visualisation and machine learning using Python. Learn how to use R Shiny and Leaflet for creating interactive maps. ***Curriculum breakdown of Spatial Analysis in ArcGIS*** Module 01: Point Density Analysis Module 02: Raster Calculator and Vector Isolation Module 03: Raster to Topography Module 04: Raster Reclassification Module 05: Raster Overlay Module 06: Slope Analysis and Hydrology tools Module 07: Introduction to TIFF Files Module 08: Introduction to 3D Surfaces Module 09: Satellite Images and TIN Surfaces Module 10: Exercise How is the Spatial Analysis in ArcGIS Bundle Assessment Process? You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you successfully pass the exams CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals looking to expand their skill set in the field of spatial analysis. Graduates seeking to enhance their employability in the GIS industry. Individuals seeking to understand spatial data analysis for research purposes. Students pursuing a degree in GIS or a related field. Career path This bundle will be beneficial for anyone looking to pursue a career as: GIS Analyst: £22,000 - £35,000 per annum. GIS Developer: £30,000 - £50,000 per annum. Spatial Data Scientist: £30,000 - £70,000 per annum. Data Analyst: £25,000 - £40,000 per annum. Business Intelligence Analyst: £35,000 - £60,000 per annum. Hydrologist: £25,000 - £40,000 per annum. Certificates Award in Spatial Analysis in ArcGIS at QLS Level 2 Hard copy certificate - Included After successfully completing the course, you can order an original hardcopy Certificate of Achievement endorsed by the Quality Licence Scheme. This certificate will be delivered to your home, free of charge. To obtain the additional Quality Licence Scheme Endorsed Certificate, you will need to pay the corresponding fee based on the level of the courses: Level 1: £59 Level 2: £79 Level 3: £89 Level 4: £99 Level 5: £119 Level 6: £129 Level 7: £139 CPD QS Accredited Certificate Digital certificate - £10 Upon successfully completing the Bundle, you will need to place an order to receive a PDF Certificate for each course within the bundle. These certificates serve as proof of your newly acquired skills, accredited by CPD QS and will cost you £10 for each course. Also, the certificates are recognised throughout the UK and internationally. CPD QS Accredited Certificate Hard copy certificate - £29 International students are subject to a £10 delivery fee for their orders, based on their location.

FREE QLS Level 7 Hard Copy Certificate | 180 CPD Points | Lifetime Access | Installment Payment | Tutor Support

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

Leading Cross-Cultural Virtual Teams (On-Demand) High-performing teams are a must in this world of intense competition and higher expectations. Global virtual teaming has become a necessity as organizations become increasingly distributed and suppliers and clients actively engage in joint projects. Teams work across geographical and organizational boundaries to deliver solutions and services to global users where distance and differences, both geographic and cultural, amplify the effect of issues and factors that are relatively straightforward when managing a team of people in the same location. This course delivers practical concepts and techniques that participants will start using immediately on their global projects. What you will Learn At the end of this program, you will be able to: Define relationships among foundational concepts (leadership and three dimensions of diversity) and explain their potential impacts on project performance Describe key components of successful project leadership and build selected Transformational Leadership skills Prepare to convert project challenges stemming from personal or cultural diversity into potential competitive advantage Implement selected best practices to meet key challenges facing virtual project teams Foster and grow an environment that supports continued success for CCVTs Getting Started Foundation Concepts Basic definitions Critical success factors for leading cross-cultural virtual teams (CCVTs) A roadmap to success for leading CCVTs Leadership Excellence in Any Project Environment Leading effectively in a global environment Transformational leadership The four components of Transformational Leadership Leveraging Personal Diversity Overview of personal diversity Mind styles The theory of multiple intelligences Connecting Transformational Leadership and personal diversity Embracing Cultural Diversity Introduction to cultural intelligence The impact of culture Cultural Dimensions Theory The Culture Map Managing Virtual Diversity Overview of virtual diversity Virtual time management Virtual processes and technology Virtual leadership Creating an Environment for Success Supporting a cross-cultural virtual-team (CCVT-) friendly environment Building a foundation of trust Developing a team charter Recap and review Summary and Next Steps Personal action plan

Become a certified Tableau Data Analyst through our Data Analytics course. Gain the skills to analyze and visualize data using Tableau.

Behaviour Management: Behaviour Management Course Online Are you looking for Level 2 Behaviour Management in the Early Years? We have created the greatest Level 2 Behaviour Management in the Early Years, which will teach you the knowledge and skills necessary to address concerns pertaining to care settings. This Behaviour Management: Behaviour Management Course explains the factors affecting behaviours. Also, this Level 2 Behaviour Management in the Early Years course teaches the learning styles of various age groups childrens. Moreover, the role of an adult is explained in this Level 2 Behaviour Management in the Early Years course. You will learn about positive behaviour and handling strategies. Overall, this Level 2 Behaviour Management in the Early Years course is helpful for you to enhance your knowledge of child development. Join in our Behaviour Management: Behaviour Management Course programme to realise your full potential in working with kids! Learning outcome of Behaviour Management: Behaviour Management Course After completing this Level 2 Behaviour Management in the Early Years course, learner will know about: The factors affecting behaviours from this Level 2 Behaviour Management in the Early Years course. This Level 2 Behaviour Management in the Early Years teaches the learning styles of childrens. The role of the adult is also described in Level 2 Behaviour Management in the Early Years course. This Level 2 Behaviour Management in the Early Years describes positive behaviour strategies. Main Course: Level 2 Behaviour Management in the Early Years Course Free Courses are including with this Behaviour Management: Behaviour Management Course Along with The Behaviour Management Course, We Offer a free Life Coaching Course Along with The Behaviour Management Course, We Offer a free Emotional Intelligence Course Special Offers of this Behaviour Management: Behaviour Management Course This Behaviour Management Course includes a FREE PDF Certificate. Lifetime access to this Behaviour Management Course Instant access to this Behaviour Management Course Get FREE Tutor Support to this Behaviour Management Course Behaviour Management: Behaviour Management Course Online Students who complete this course on behavior management will have a solid understanding of the variables that influence behavior, learning preferences, the adult role, and constructive behavior techniques. After completing this course on behavior management, learners will understand why kids misbehave and how to properly accommodate their needs and learning preferences. Who is this course for? Behaviour Management: Behaviour Management Course Online The Behaviour Management: Behaviour Management Course programme is designed especially for people who want to work as licensed child care managers or leaders. Requirements Behaviour Management: Behaviour Management Course Online To enrol in this Behaviour Management Course, students must fulfil the following requirements. To join in our Behaviour Management Course, you must have a strong command of the English language. To successfully complete our Behaviour Management Course, you must be vivacious and self driven. To complete our Behaviour Management Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Behaviour Management Course. Career path Behaviour Management: Behaviour Management Course Online After completing this Behaviour Management: Behaviour Management Course credential successfully, learners can work in childcare facilities in a range of capacities.

The course is crafted to reflect the most in-demand workplace skills. It will help you understand all the essential concepts and methodologies with regards to PySpark. This course provides a detailed compilation of all the basics, which will motivate you to make quick progress and experience much more than what you have learned.

Unlock the secrets of effective leadership and people management with our People Management & Leadership Diploma. Dive into essential topics such as emotional intelligence, team building, conflict resolution, and more.

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.

Description Educational psychology Diploma Educational psychology relates to the manner in which students learn and develop. It focuses on aspects such as diversity and development in education. Educational psychology is the base upon which the method of teaching is built. And it is essential to hone the skills of trainers and teachers in their profession. Educational psychology gives a foundation for trainers and teachers to organize their teaching job in a coherent and more professional manner. It also helps them evaluate the learning process of each student. The educational system gives a whole lot of chances for psychologists. Since most crucial emotional issues happen in the life of a child's formative years, most primary schools hire psychologists who are equipped in clinical psychology, child development, education and the ability to assess a child's emotional and learning problems. After thoroughly consulting with teachers and parents they come up with plans to help the children in and out of the classroom. The Online Educational Psychology Course provides a deeper understanding of human learning, such as the methods to understand, learn, motivate, etc. It shows the relevance of an approach that is based on evidence in educational psychology and the obstructions it faces in reality. It also discusses concepts like instructional psychology, intelligence, inclusion, etc. Also, the course gives detailed information on matters of school phobia, dyslexia, classroom behaviour, autism, bullying, etc. Educational psychology helps educators to understand various learning and teaching situations and the various abilities, needs, interests, and intelligence of the students or learners. This helps them better their own instructional approaches and skills in such a way that improves the learning processes and experiences. This Educational psychology Diploma equips students with better ideas on educational psychology, its models, practices, theories, approaches and methods. This helps them identify and adapt workable learning and teaching approaches. The course can be ideal for those who are eager to get an idea as to how people take in and keep information. This Educational psychology Diploma course can also be pursued by those who aspire to become educators. What you will learn 1: Introduction to Educational Psychology 2: Learning, Cognition, and Memory 3: Learning in Context 4: Complex Cognitive Processes 5: Cognitive Development 6: Motivation and Affect 7: Personal, Social, and Moral Development 8: Instructional Strategies 9: Strategies for Creating an Effective Classroom Environment 10: Assessment Strategies Course Outcomes After completing the course, you will receive a diploma certificate and an academic transcript from Elearn college. Assessment Each unit concludes with a multiple-choice examination. This exercise will help you recall the major aspects covered in the unit and help you ensure that you have not missed anything important in the unit. The results are readily available, which will help you see your mistakes and look at the topic once again. If the result is satisfactory, it is a green light for you to proceed to the next chapter. Accreditation Elearn College is a registered Ed-tech company under the UK Register of Learning( Ref No:10062668). After completing a course, you will be able to download the certificate and the transcript of the course from the website. For the learners who require a hard copy of the certificate and transcript, we will post it for them for an additional charge.