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Course Overview Do you know, effective use of data structure can increase the efficiency of your software design process? To create efficient algorithms and continue a smooth software design process Data Structure is one of the most fundamental ingredients. Learn the basics of data structure and how you can use them from this Easy to Advanced Data Structures Masterclass course and create incredible software designs using that knowledge. This Easy to Advanced Data Structures Masterclass course will help you to strengthen your basics, clear misunderstandings and get hold of the functions of data structure and how you can use it. The animated video lessons will help you understand data Structure easily. You will learn about Static and dynamic arrays, linked lists, stacks, queues, search trees, hash tables, sparse tables and many other functions that will help you understand how you can use data structure and create efficient software designs. Learning Outcomes Understand the basics of data structure Familiarize with the algorithms associated with data structure Be able to include linked lists, dynamic arrays, queues and stacks in your data structure project Learn what Static and dynamic arrays are Be able to Union or disjoint sets in your data table Get a clear understanding of hash tables and how they work Who is this course for? This course is ideal for anyone who wants to learn about data structure or strengthen their basics. It is especially helpful for those who work in the IT industry and deal with database management. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path Easy to Advanced Data Structures Masterclass is a useful qualification to possess and would be beneficial for any related profession or industry such as: Software Engineers Programmers Web Designers Web Developers App Developers Unit 01: Introduction Module 01: Promo Video 00:02:00 Module 02: Data Structure Introduction 00:05:00 Module 03: Computational Complexity Analysis 00:13:00 Unit 02: Arrays Module 01: Static and Dynamic Arrays 00:12:00 Module 02: Dynamic Arrays Source Code 00:07:00 Unit 03: Linked List Module 01: Singly and Doubly Linked Lists 00:15:00 Module 02: Doubly Linked Lists Source Code 00:10:00 Unit 04: Stack Module 01: Stack 00:12:00 Module 02: Stack Implementation 00:04:00 Module 03: Stack Source Code 00:04:00 Unit 05: Queues Module 01: Queues (Part-1) 00:06:00 Module 02: Queues (Part-2) 00:06:00 Module 03: Queue Source Code 00:04:00 Unit 06: Priority Queues (PQs) Module 01: Priority Queues (PQs) with an interlude on heaps 00:13:00 Module 02: Turning Min PQ into Max PQ 00:06:00 Module 03: Adding Elements to Binary Heap 00:10:00 Module 04: Removing Elements from Binary Heap 00:14:00 Module 05: Priority Queue Binary Heap Source Code 00:16:00 Unit 07: Union Find Module 01: Disjoint Set 00:06:00 Module 02: Kruskal's Algorithm 00:06:00 Module 03: Union and Find Operations 00:11:00 Module 04: Path Compression Union Find 00:07:00 Module 05: Union Find Source Code 00:08:00 Unit 08: Binary Search Trees Module 01: Binary Trees and Binary Search Trees (BST) 00:13:00 Module 02: Inserting Element into a Binary Search Tree (BST) 00:06:00 Module 03: Removing Element from a Binary Search Tree (BST) 00:14:00 Module 04: Tree Traversals 00:12:00 Module 05: Binary Search Source Code 00:13:00 Unit 09: Fenwick Tree Module 01: Fenwick Tree Construction 00:06:00 Module 02: Point Updates 00:05:00 Module 03: Binary Indexed Tree 00:14:00 Module 04: Fenwick Tree Source Code 00:06:00 Unit 10: Hash Tables Module 01: Hash Table 00:17:00 Module 02: Separate Chaining 00:08:00 Module 03: Separate Chaining Source Code 00:12:00 Module 04: Open Addressing 00:11:00 Module 05: Linear Probing 00:14:00 Module 06: Quadratic Probing 00:09:00 Module 07: Double Hashing 00:15:00 Module 08: Removing Element Open Addressing 00:08:00 Module 09: Open Addressing Code 00:15:00 Unit 11: Suffix Array Module 01: Introduction 00:03:00 Module 02: The Longest Common Prefix (LCP) Array 00:03:00 Module 03: Using SA/LCP Array to Find Unique Substrings 00:05:00 Module 04: Longest Common Substring (LCS) 00:11:00 Module 05: Longest Common Substring (LCS) Full Example 00:07:00 Module 06: Longest Repeated Substring (LRS) 00:05:00 Unit 12: AVL Trees Module 01: Balanced Binary Search Trees (BBSTs) 00:09:00 Module 02: Inserting Elements into an AVL Tree 00:10:00 Module 03: Removing an AVL Tree 00:09:00 Module 04: AVL Tree Source Code 00:17:00 Unit 13: Indexed Priority Queue Module 01: Indexed Priority Queue (Part-1) 00:25:00 Module 02: Indexed Priority Queue Source Code 00:09:00 Unit 14: Sparse Tables Module 01: Sparse Table 00:26:00 Module 02: Sparse Table Source Code 00:07:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description Data Science Diploma Introducing the Data Science Diploma, an online course tailored for those eager to step into the dynamic world of data science. This comprehensive programme ensures participants grasp the essence of contemporary data science techniques, tools, and theories. At the core of this Data Science Diploma is the module titled Foundations of Data Science. It sets the groundwork by instilling fundamental principles, thereby preparing learners to navigate the expansive sea of data efficiently and effectively. As one progresses, the intricate elements of Data Engineering and Big Data come into play, elucidating how vast amounts of data are managed, stored, and processed. An essential aspect of data science lies in understanding uncertainty and making informed decisions. To this end, Probability and Statistics in Data Science offers learners the tools to decipher patterns, predict trends, and make data-driven decisions. Following closely, Clustering and Classification Techniques provide a deep understanding of how to categorise data into specific groups based on inherent characteristics, paving the way for more precise analysis. But what's data science without the necessary mathematical prowess? The Advanced Mathematical Modeling module hones this skill, enabling learners to craft intricate models that can simulate real-world scenarios. Such models act as the backbone of various data analyses and offer a detailed understanding of the underlying processes. The saying, 'A picture is worth a thousand words,' holds especially true in data science. With the Data Visualisation Principles and Design module, learners are equipped with the knowledge to translate complex data into visually compelling stories. This understanding is further solidified with the Web-Based Data Visualisation Tools, offering hands-on experience in using cutting-edge tools to portray data visually. The course recognises the growing demand for intuitive dashboards that provide real-time insights. The Dashboard Design and Mapping module aids participants in creating interactive and user-friendly dashboards, ensuring stakeholders get a clear and concise view of the data. Yet, as one manoeuvres through these diverse modules, a foundational understanding of computing becomes paramount. Hence, Computing for Data Science takes centre stage, familiarising learners with the computational aspects of data analysis, from algorithms to data structures. Concluding the Data Science Diploma is the module on Domain-Specific Data Science Applications. This segment offers a glimpse into how data science principles are applied across different sectors, from healthcare to finance. It accentuates the versatility of data science, proving its indispensable nature in today's digitised world. To sum up, this online Data Science Diploma ensures a holistic understanding of data science. By intertwining theory with practical application, it equips learners with the skill set required to thrive in the data-driven industries of tomorrow. So, if the realm of data beckons you, this diploma is your gateway to excellence. What you will learn 1:Foundations of Data Science 2:Data Engineering and Big Data 3:Probability and Statistics in Data Science 4:Clustering and Classification Techniques 5:Advanced Mathematical Modeling 6:Data Visualisation Principles and Design 7:Web-Based Data Visualisation Tools 8:Dashboard Design and Mapping 9:Computing for Data Science 10:Domain-Specific Data Science Applications 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.

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Overview This comprehensive course on Quick Data Science Approach from Scratch will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Quick Data Science Approach from Scratch comes with accredited certification from CPD, 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 Quick Data Science Approach from Scratch. It is available to all students, of all academic backgrounds. Requirements Our Quick Data Science Approach from Scratch 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 4 sections • 15 lectures • 01:00:00 total length •Introduction: 00:02:00 •Data Science Explanation: 00:05:00 •Need of Data Science: 00:02:00 •8 Common mistakes by Aspiring Data Scientists/Data Science Enthusiasts: 00:08:00 •Myths about Data Science: 00:03:00 •Data Types and Variables: 00:04:00 •Descriptive Analysis: 00:02:00 •Data Cleaning: 00:02:00 •Feature Engineering: 00:02:00 •Data Thinking Development: 00:03:00 •Problem Definition: 00:05:00 •Algorithms: 00:14:00 •Prediction: 00:03:00 •Learning Methods: 00:05:00 •Assignment - Quick Data Science Approach from Scratch: 00:00:00

If you have already covered the basics of Python in programming, you know it already that it is

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Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: Apply descriptive statistics, distributions, and probability theory to summarise and visualise data Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data Use Python and R to implement statistical and machine learning methods Interpret and communicate the results of your analysis using appropriate metrics and visualisations Solve real-world problems and scenarios using statistics and probability Why choose this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course for? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge Students and researchers who want to learn the mathematical foundations of data science and machine learning Professionals and managers who want to understand and apply data-driven decision making Hobbyists and enthusiasts who want to explore and learn from data Anyone who loves statistics and probability and wants to challenge themselves Career path Data Scientist (£35,000 - £55,000) Machine Learning Engineer (£40,000 - £60,000) Statistician (£35,000 - £55,000) Data Analyst (£40,000 - £60,000) Business Intelligence Analyst (£45,000 - £65,000) Senior Data Analyst (£50,000 - £70,000) Prerequisites This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Description Fundamentals of Artificial Intelligence diploma  Artificial intelligence is widely popular and fascinates most people, especially when compared to technology-related topics. The reason behind it may be that it often goes and wanders beyond what we can imagine. We live in a world where we constantly hold smartphones capable of performing tasks we could never have even thought of just ten years ago. We use technological innovations every day, like voice commands, facial recognition, and other tools that can isolate portraits or take group photos. These are things we never imagined were possible, but we have grown used to them today. We have experienced the wonders of AI, and every new aspect awes us. Although technology has become a part of our daily lives, most do not know how it works. Looking at how amazing the effects of AI are, there is no doubt that the way it works will awe us just as much. Narrow AI is more common, which is AI meant to be used powerfully in one case, like AI for facial recognition or detection of spam. AI systems can be used to sort out vast piles of data like recommendation systems and search engines. They can also provide insights into the data. With this kind of narrow AI, it is expected that it can only perform what it is designed to do. A program meant to detect spam or recognize facial features cannot also be expected to play chess, compose songs, and record shows to watch in the future. The Fundamentals of Artificial Intelligence diploma course aims to remove AI's mystery so that the learners can develop a better in-depth understanding of the technology. The Fundamentals of Artificial Intelligence diploma course consists of an introduction that includes all the basic concepts in AI that will enable you to see what things are possible and what are not within the technology. It will also help you understand the effects of AI on our daily lives. After completing the Fundamentals of Artificial Intelligence diploma course, you will be able to define AI, discuss it, evaluate AI claims, explain the technologies that underpin AI, such as neural networks and machine learning, and understand the main implications of AI. The Fundamentals of Artificial Intelligence diploma course will also discuss AI's concerns and issues like biases, ethics, and jobs. You will also get expert advice regarding learning about AI and beginning a profession in AI-related fields. The fundamentals of Artificial Intelligence diploma does not demand that you have any expertise in computer science or programming. It is simply meant to introduce to you the essentials and basics in the field, regardless of whether you possess a technical background. We aim to encourage as many people as possible from all backgrounds to learn about artificial intelligence, what it is, what it can or cannot do, and how one can start creating methods of AI. The course is flexible and can be studied and completed at whatever pace you are comfortable with. What you will learn   1: An introduction to AI and data  2: Algorithms and Hardware  3: Uses of AI in computer applications and common processes  4: Using AI for medical needs  5: AI helping improve human interactions  6: Data analysis for AI  7: Machine learning and deep learning in AI  8: AI in hardware applications  9: AI as a nonstarter  10: AI in outer space  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.

Description Robotics Fundamentals Diploma Introducing the Robotics Fundamentals Diploma, an innovative online course tailored for those keen on learning the nuances of modern robotics. This programme is an unparalleled journey into the captivating world of machines, sensors, and algorithms that are shaping the future. Begin with a comprehensive introduction to robotics, setting a solid foundation for your studies. Grasping the basics is paramount, and this diploma ensures learners obtain a deep understanding of these core principles. Next, the course navigates the broader expanse of robotics fundamentals. Here, individuals grasp the intricacies that lie at the heart of these machines. Every robot, from the simplest to the most complex, relies on sensors and actuators. Delving into this topic, this diploma teaches students about their pivotal role in robotics. From sensing external stimuli to initiating precise movements, these components are the nerve centres of any robotic system. The beauty of a robot lies in its movements. Thus, the segments on mechanisms and kinematics elucidate the physical aspects that contribute to their agile motion. Pair this with a detailed analysis of the dynamics and control of robots, and one gets a holistic view of how these machines function and interact with their surroundings. But, how do robots determine their course of action? That's where the module on path planning and navigation comes into play. It allows learners to comprehend how robots chart their routes and avoid obstacles, ensuring smooth and efficient operations. Manipulation and grasping are fundamental robotic tasks, especially in industrial settings. This diploma elaborates on the strategies and techniques robots use to handle objects, ensuring they can efficiently interact with the physical world around them. As we delve further into the modern realm of robotics, the role of computer vision becomes unmistakably evident. This course unravels its significance, showcasing how robots perceive and interpret visual information, ensuring accurate responses to their environment. In today's age, no study of robotics is complete without addressing artificial intelligence and machine learning. These are the cognitive components that arm robots with 'thinking' capabilities. This module of the Robotics Fundamentals Diploma delves deep into the integration of these technologies in robotics, offering insights into how machines learn, adapt, and make decisions. Lastly, as with any forward-looking course, the programme concludes with a session on emerging trends and applications of robotics. From healthcare to space exploration, learners are acquainted with the innovative ways robots are being employed to redefine the boundaries of possibility. In summary, the Robotics Fundamentals Diploma offers a comprehensive online learning experience. Whether you're a budding engineer, a tech enthusiast, or simply someone curious about the robotic world, this course promises to equip you with the knowledge and skills necessary to navigate this ever-evolving landscape. Sign up today and embark on an enlightening journey into the realm of robotics. What you will learn 1:Introduction to Robotics 2:Robotics Fundamentals 3:Sensors and Actuators in Robotics 4:Mechanisms and Kinematics 5:Dynamics and Control of Robots 6:Path Planning and Navigation 7:Manipulation and Grasping 8:Computer Vision in Robotics 9:Artificial Intelligence and Machine Learning in Robotics 10:Emerging Trends and Applications of Robotics 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.