978 Data Science courses in Leicester delivered Online

Overview This comprehensive course on Spatial Data Visualization and Machine Learning in Python Level 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Spatial Data Visualization and Machine Learning in Python Level 4 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? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Spatial Data Visualization and Machine Learning in Python Level 4. It is available to all students, of all academic backgrounds. Requirements Our Spatial Data Visualization and Machine Learning in Python Level 4 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 8 sections • 21 lectures • 04:40:00 total length •Introduction: 00:14:00 •Python Installation: 00:03:00 •Installing Bokeh: 00:04:00 •Data Preparation: 00:24:00 •Creating a Bar Chart: 00:18:00 •Creating a Line Chart: 00:12:00 •Creating a Doughnut Chart: 00:22:00 •Creating a Magnitude Plot: 00:31:00 •Creating a Geo Map Plot: 00:20:00 •Creating a Grid Plot: 00:12:00 •Data Pre-processing: 00:21:00 •Building a Predictive Model: 00:21:00 •Building a Prediction Dataset: 00:07:00 •Adding predicted data to our plots - Part 1: 00:13:00 •Adding predicted data to our plots - Part 2: 00:14:00 •Adding predicted data to our plots - Part 3: 00:15:00 •Adding the Grid Plot: 00:08:00 •Installing Visual Studio Code: 00:01:00 •Creating the Project and Virtual Environment: 00:08:00 •Building and Running the Server: 00:12:00 •Resources: 00:00:00

Learn Python 3 programming fast!

This course will help you to learn the basic concepts of Python programming. From understanding variables to functions and debugging the programs to exception handling, you will master it all with the help of engaging exercises and projects.

Take your Python skills to the next level. Learn how expert programmers work with code and the techniques they use.

Learn Flask, the simple yet powerful Python web framework. This course is a ridiculously simple way to learn Flask in less than a weekend.

REST or RESTful API design (Representational State Transfer) is designed to take advantage of existing protocols. Django REST framework is a powerful and flexible toolkit to build web APIs. Throughout the course, we will explore the most important Django Rest framework topics step-by-step. We will learn topics such as API basics, serializers, class-based views, and so on to build flexible APIs.

Learn about automated software testing with Python, BDD, Selenium WebDriver, and Postman, focusing on web applications

Advance your data skills by mastering Spark programming in Python. This beginner's level course will help you understand the core concepts related to Apache Spark 3 and provide you with knowledge of applying those concepts to build data engineering solutions.

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.

Javascript for Data Structures Course Overview This course, JavaScript for Data Structures, offers a comprehensive introduction to fundamental data structures using JavaScript. Learners will explore core concepts such as lists, stacks, queues, and sets, gaining a solid understanding of how data is organised and managed in programming. The course emphasises clear, logical thinking and problem-solving skills applicable to software development, data analysis, and computer science. By the end, participants will be able to implement key data structures effectively, enhancing their coding proficiency and preparing them for more advanced programming challenges or career opportunities in technology-related fields. Course Description This course delves into essential data structures within JavaScript, providing detailed coverage of lists, stacks, queues, and sets. Learners will study how these structures operate, their use cases, and how to manipulate them efficiently in code. The curriculum is designed to develop both theoretical understanding and coding ability through structured explanations and examples. Throughout the course, students will develop skills in data organisation, algorithmic thinking, and memory management principles. This knowledge is critical for writing optimised code and tackling complex computational problems in software development and data science domains. Javascript for Data Structures Curriculum Module 01: Introduction Module 02: Essential Concepts Module 03: List Data Structure Module 04: Stack Data Structure Module 05: Queue Data Structure Module 06: Set Data Structure Module 07: Final Thought (See full curriculum) Who Is This Course For? Individuals seeking to build strong foundations in data structures using JavaScript. Professionals aiming to enhance their software development skills. Beginners with an interest in programming and computer science. Students preparing for technical roles in coding or data analysis. Career Path Software Developer Front-End Developer Data Analyst Junior Programmer Computer Science Student