239 Data Structures & Algorithms (DSA) courses

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This course will teach you how to work with object recognition using a predefined dataset and how to create a custom dataset. The course will also teach you to train the You Only Look Once (YOLO) model to build a coronavirus detection model.

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Welcome to this dual-phase course. In the first segment, we delve into neural networks and deep learning. In the second, ascend to mastering Generative Adversarial Networks (GANs). No programming experience required. Begin with the fundamentals and progress to an advanced level.

This course offers a swift and straightforward way to learn Python programming. It is thoughtfully designed, packed with hands-on exercises, and tailored to assist you in embarking on your Python 3 journey. No prior programming experience is necessary to enroll in this course.

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.

Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

Learn BDD with SpecFlow (based on Gherkin) and Selenium WebDriver with C# alongwith an Intro to UnitTesting and TDD with TestStack.White