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About this Training Course There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil & Gas industry. In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided. This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results. Training Objectives By attending this course, participants will be able to acquire the following: Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these. Be able to communicate more effectively with staff in other disciplines. Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation. Gain an awareness of modern seismic technology. Apply the learning in a series of practical, illustrative exercises. Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&P activities Target Audience The blended course is intended for non-geophysicists who have intensive interaction with geophysicists. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests. Course Level Intermediate Trainer Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone. After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments. After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht. From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods. After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies. In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

This course is designed around three main activities for getting better results with deep learning models: better or faster learning, better generalization to new data, and better predictions when using final models. Take this course if you're passionate about deep learning with a solid foundation in this space and want to learn how to squeeze the best performance out of your deep learning models.

This course will help you prepare for the AI-900 Exam: Microsoft Azure AI Fundamentals. We will cover the complete exam syllabus as updated in April 2021 with sample questions.

In the ever-evolving landscape of healthcare IT in the UK, recent challenges have underscored the critical need for skilled professionals. The CompTIA Healthcare IT Technician course offers a comprehensive solution to address these issues head-on. With a curriculum designed to equip you with a robust skill set, this course seamlessly integrates CompTIA Network, A+, CySA+, PenTest+, Cloud+, ITF+, Security+, GDPR Training, and more. From mastering the intricacies of network security to delving into machine learning basics, this CompTIA Healthcare IT Technician course empowers you with a diverse skill set crucial for today's IT challenges. This CompTIA Healthcare IT Technician Bundle Consists of the following Premium courses: Course 01: CompTIA Healthcare IT Technician Course 02: CompTIA Network Course 03: Diploma in CompTIA A+ Course 04: CompTIA CySA+ Cybersecurity Analyst Course Course 05: CompTIA PenTest+ (Ethical Hacking) course Course 06: CompTIA Cloud+ (CV0-002) Course 07: CompTIA ITF+ (FCO-U61) Course 08: CompTIA Security+ Course 09: CompTIA Network+ Certification (N10-007) Course 10: GDPR Training Course 11: Introduction to Computers and Internet for Beginners Course 12: Data Science and Visualisation with Machine Learning Course 13: Machine Learning Basics Course 14: Excel Add-in with C# VSTO and Web Course 15: SQL Database Administrator Course 16: Computer Operating System and Troubleshooting Course 17: Web Application Penetration Testing Course Course 18: Wordpress Web Development Course 19: Computer Science with Python Course Course 20: International Healthcare Policy 10 Extraordinary Career Oriented CompTIA Healthcare IT Technician courses that will assist you in reimagining your thriving techniques- Course 01: Effective Communication Skills Diploma Course 02: Business Networking Skills Course 03: Influencing and Negotiation Skills Course 04: Delegation Skills Training Course 05: Time Management Course 06: Leadership Skills Training Course 07: Decision Making and Critical Thinking Online Course Course 08: Emotional Intelligence and Social Management Diploma Course 09: Assertiveness Skills Course 10: Touch Typing Complete Training Diploma Learning Outcomes of CompTIA Healthcare IT Technician: Upon completion of this CompTIA Healthcare IT Technician bundle, you should be able to: Implement advanced network security measures for healthcare infrastructures. Analyze and counter cybersecurity threats with precision. Conduct ethical hacking and penetration testing for web applications. Master the complexities of GDPR compliance in healthcare settings. Develop expertise in cloud computing within healthcare frameworks. Demonstrate proficiency in machine learning for data analysis in healthcare. As technology becomes the heartbeat of healthcare, this CompTIA Healthcare IT Technician course ensures you're at the forefront of innovation. Unleash your potential in web application penetration testing, hone your WordPress web development skills, and navigate the world of data science with confidence. Whether you're troubleshooting computer operating systems or safeguarding networks through ethical hacking, this course primes you for success in the dynamic healthcare IT arena. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? IT professionals aspiring to specialize in healthcare technology. Individuals keen on advancing their skills in ethical hacking. Tech enthusiasts seeking expertise in cloud computing and cybersecurity. Data enthusiasts interested in applying machine learning in healthcare. Those desiring to excel in network administration and troubleshooting. Individuals looking to carve a niche in web application development. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Requirements To participate in this CompTIA Healthcare IT Technician course, all you need is - A smart device A secure internet connection And a keen interest in CompTIA Healthcare IT Technician Career path CompTIA Healthcare IT Technician - •45,000 Cybersecurity Analyst - •50,000 Penetration Tester - •55,000 Cloud Solutions Architect - •60,000 Data Science Analyst - •50,000 Network Administrator - •40,000 Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free

Learn to build highly sophisticated deep learning and Computer Vision applications with PyTorch

This course is about developing core skills that will stay with you for a lifetime. It is designed such that you can watch the material and follow along step-by-step. It focuses on the implementation of YOLOv4 to get you up and running. You'll be an object detecting ninja in no time and be able to graduate to more advanced content.

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.

24-Hour Knowledge Knockdown! Prices Reduced Like Never Before Are you fascinated by the potential of AI to revolutionise our world? The UK government has pledged £1 billion to invest in AI research, creating exciting job opportunities in this dynamic field. If you're curious about how AI works and want to explore its practical applications, this Artificial Intelligence, Open AI & ChatGPT bundle is for you! With this Artificial Intelligence, Open AI & ChatGPT course you will get 20 CPD Accredited PDF Certificates, Hard Copy Certificate of Project on Deep Learning - Artificial Neural Network and our exclusive student ID card absolutely free. Courses Are Included In This Artificial Intelligence, Open AI & ChatGPT Bundle: Course 01: Project on Deep Learning - Artificial Neural Network Course 02: Deep Learning & Neural Networks Python - Keras Course 03: Machine Learning Basics Course 04: Hands on Machine Learning Project - Auto Image Captioning for Social Media Course 05: Statistics & Probability for Data Science & Machine Learning Course 06: Hands on Deep Learning Projects - Stock price Prognostics Course 07: Deep Learning Projects - Convolutional Neural Network Course 08: Deep Learning Projects - Handwritten Digit Recognition Using Neural Network Course 09: Essential Training on Deep Learning Heuristic using R Course 10: Project on Deep Learning - Artificial Neural Network Course 11: Machine Learning with Python Course Course 12: Python Data Science Course 13: Quick Data Science Approach from Scratch Course 14: Data Science & Machine Learning with R Training Course 15: Azure Machine Learning Course 16: A Beginner Crash Course on ChatGPT Course 17: ChatGPT Complete Guide with Expertise Course 18: ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! Course 19: ChatGPT for Marketing and Productivity with AI Tools Course 20: Fundamentals to Identifying Market Trends You Can Capitalise On This comprehensive Artificial Intelligence, Open AI & ChatGPT bundle equips you with the essential skills to thrive in the AI revolution. You'll learn about deep learning, building powerful neural networks that can learn and adapt like the human brain. Master Python, the language of Artificial Intelligence, and explore practical applications like image captioning and stock price prediction. Learning Outcomes Understand the foundational concepts of artificial intelligence and machine learning techniques. Gain hands-on experience with deep learning projects and their practical applications. Learn to implement machine learning algorithms using Python and R programming languages. Develop skills in data science and statistical analysis for informed decision-making. Master ChatGPT functionalities for marketing and productivity enhancements. Explore market trends and develop strategies to leverage AI tools effectively. Don't miss this chance to elevate your career and skillset. Enrol in Artificial Intelligence, Open AI & ChatGPT today and take the first step towards achieving your goals and dreams. Why buy this Artificial Intelligence, Open AI & ChatGPT? Free CPD Accredited Certificate upon completion of Artificial Intelligence, Open AI & ChatGPT Get a free student ID card with Artificial Intelligence, Open AI & ChatGPT Lifetime access to the Artificial Intelligence, Open AI & ChatGPT course materials Get instant access to this Artificial Intelligence, Open AI & ChatGPT course Learn Artificial Intelligence, Open AI & ChatGPT from anywhere in the world 24/7 tutor support with the Artificial Intelligence, Open AI & ChatGPT course. Artificial Intelligence, Open AI & ChatGPT is an entirely online, interactive lesson with voiceover audio. Start your learning journey straightaway with our Artificial Intelligence, Open AI & ChatGPT Training! This Artificial Intelligence's curriculum has been designed by Artificial Intelligence experts with years of Artificial Intelligence experience behind them. The Artificial Intelligence course is extremely dynamic and well-paced to help you understand Artificial Intelligence with ease. You'll discover how to master the Artificial Intelligence skill while exploring relevant and essential topics. *** Course Curriculum *** Course 01: Project on Deep Learning - Artificial Neural Network Section 01: Introduction Section 02: ANN Installation Section 03: Data Preprocessing Section 04: Data Encoding Section 05: Steps to Build ANN Section 06: Predictions and Imbalance-Learn Certification of Artificial Intelligence, Open AI & ChatGPT You have to complete the assignment given at the end of the Artificial Intelligence, Open AI & ChatGPT 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. After passing the Artificial Intelligence, Open AI & ChatGPT exam You will be entitled to claim a PDF & Hardcopy certificate accredited by CPD Quality standards completely free. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Artificial Intelligence, Open AI & ChatGPT course is ideal for: Students seeking mastery in Artificial Intelligence, Open AI & ChatGPT Professionals seeking to enhance Artificial Intelligence, Open AI & ChatGPT skills Individuals looking for a Artificial Intelligence, Open AI & ChatGPT-related career. Anyone passionate about Artificial Intelligence, Open AI & ChatGPT Requirements This Artificial Intelligence, Open AI & ChatGPT doesn't require prior experience and is suitable for diverse learners. Career path This Artificial Intelligence, Open AI & ChatGPT bundle will allow you to kickstart or take your career in the related sector to the next stage. Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited Hard copy certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

Recent developments in data analytics and statistics underscore the critical importance of understanding both data structure and analytics methodologies in today's data-driven world. With the exponential growth of data, businesses are increasingly relying on skilled professionals who can harness the power of data to drive informed decision-making. Our comprehensive Data Structure, Data Analytics with Statistics & Data Science QLS Endorsed Diploma bundle, endorsed by the Quality Licence Scheme (QLS) and accredited by the CPD Quality Standards (QS), offers a holistic approach to mastering data structure, data analytics, and statistical techniques. In an era where data reigns supreme, organisations seek individuals who can navigate complex datasets with confidence and precision. This Data Structure, Data Analytics bundle equips learners with the essential skills and knowledge needed to excel in the field of data science and analytics. By delving into topics such as data manipulation, statistical analysis, and database management, participants gain a deep understanding of how to extract valuable insights from raw data. Moreover, our guided courses in career development and communication empower learners to effectively communicate their findings and advance their professional journey. Bundle Include includes: QLS Endorsed Courses: Course 01: Certificate in Data Analytics with Tableau at QLS Level 3 Course 02: Diploma in Data Structure at QLS Level 5 Course 03: Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 CPD QS Accredited Courses: Course 04: Business and Data Analytics for Beginners Course 05: Learn Financial Analytics and Statistical Tools Course 06: SQL For Data Analytics & Database Development Course 07: Big Data Analytics with PySpark Power BI and MongoDB Course 08: Google Data Studio: Data Analytics Course 09: Business Intelligence Analyst Course 10: Spatial Data Visualization and Machine Learning in Python Course 11: Data Analysis In Excel Take your career to the next level with our Data Structure, Data Analytics bundle that includes technical courses and five guided courses focused on personal development and career growth. Course 12: Career Development Plan Fundamentals Course 13: CV Writing and Job Searching Course 14: Networking Skills for Personal Success Course 15: Ace Your Presentations: Public Speaking Masterclass Course 16: Decision Making and Critical Thinking Seize this opportunity to elevate your career with our comprehensive Data Structure, Data Analytics bundle, endorsed by the prestigious QLS and accredited by CPD.Data Structure, Data Analytics with Statistics & Data Science QLS Endorsed Diploma. Learning Outcomes: Upon completion of this Data Structure, Data Analytics bundle, participants will be able to: Demonstrate proficiency in data analytics tools such as Tableau, SQL, and Google Data Studio through Data Structure, Data Analytics courses. Apply statistical techniques to analyse and interpret data for informed decision-making. Design and implement data structures to efficiently store and retrieve information. Utilise machine learning algorithms for predictive analysis and pattern recognition. Develop effective communication and presentation skills to convey insights to stakeholders. Navigate career development pathways in the field of data science and analytics. This Data Structure, Data Analytics course bundle provides a deep dive into the foundational principles of data structure, data analytics, and statistical methodologies. Participants will explore the fundamental concepts of data manipulation, including sorting, searching, and storing data efficiently. Through hands-on exercises and theoretical discussions, learners will gain a solid understanding of various data structures such as arrays, linked lists, trees, and graphs, along with their applications in real-world scenarios. Moreover, the Data Structure, Data Analytics bundle encompasses a comprehensive exploration of data analytics techniques, equipping participants with the skills to extract actionable insights from complex datasets. From descriptive and inferential statistics to predictive modelling and machine learning algorithms, learners will discover how to uncover patterns, trends, and correlations within data, enabling informed decision-making and strategic planning. Throughout the Data Structure, Data Analytics course, emphasis is placed on practical applications and case studies, allowing participants to apply their knowledge to solve real-world problems in diverse domains. CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Structure, Data Analytics course is perfect for: Aspiring data analysts seeking to enhance their analytical skills acrod Data Structure, Data Analytics courses. Professionals transitioning into roles requiring proficiency in data analytics. Students pursuing careers in data science, statistics, or related fields. Business professionals looking to leverage data for strategic decision-making. Individuals interested in advancing their career prospects in the field of data analytics. Anyone seeking to gain a comprehensive understanding of data structure, analytics, and statistics. Requirements You are warmly invited to register for this bundle. Please be aware that there are no formal entry requirements or qualifications necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Upon completion of the Data Structure, Data Analytics courses, you will be able to: Data Analyst Business Intelligence Analyst Data Scientist Statistician Database Administrator Machine Learning Engineer Data Engineer Certificates 13 CPD Quality Standard Certificates Digital certificate - Included 3 QLS Endorsed Certificates Hard copy certificate - Included

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.