137 Data Skills courses in Leeds delivered On Demand

Course Overview: According to the World Economic Forum, data analysts will be among the most in-demand professions by 2025. This Basic Google Data Studio course takes you on an enlightening journey, illuminating the intricate world of Google Data Studio from the ground up.The Basic Google Data Studio course is your stepping stone into data visualisation, geo-visualization, and in-depth socio-economic analysis. With four comprehensive modules, this curriculum is crafted to impart the foundational principles and techniques of Google Data Studio, ensuring learners possess the proficiency to translate raw data into meaningful insights.Enrol Today and Start Learning! Key Features of the Course: The Basic Google Data Studio course boasts an array of appealing features, including a CPD certificate upon completion, marking your journey into mastering Google Data Studio. 24/7 Learning Assistance ensures you can absorb the course material at your own pace, whenever it suits you best. Expect exciting learning materials that make mastering data visualisation a stimulating and enjoyable endeavour. Who is This Course For? This Basic Google Data Studio course is designed for anyone inclined towards data and interested in visual storytelling. Whether you're a business owner looking to make informed decisions, a student eyeing a future in data analysis, or a data enthusiast, this course could be the perfect fit. What You Will Learn: Introduction to Google Data Studio and its features. Navigation and interface overview of Google Data Studio. Creating reports using different data sources. Converting data into visually appealing graphs and charts. Exploring geographic data visualisation techniques. Uncovering hidden geographic trends through data visualisation. Applying the learned skills to real-world socio-economic case studies. Why Enrol in This Course: This Basic Google Data Studio course consistently receives top reviews from its participants. Recently updated with the latest trends and practices in data visualisation, this course ensures you stay on top of industry shifts. By enrolling in this course, you will develop indispensable skills in data analysis and visual storytelling. Requirements: This course requires a fundamental understanding of data analysis concepts. Internet access is required to practise Google Data Studio and access course materials. Career Path: Upon completing this Basic Google Data Studio course, you can look forward to opportunities in various data-focused professions. Such as Data Analyst Business Intelligence Developer Marketing Analyst SEO Specialist Data Scientist Data Visualisation Specialist Report Analyst In the UK, these roles offer attractive salary packages ranging from £25,000 for entry-level positions to over £60,000+ for more advanced roles. Certification: Upon successful completion of the Basic Google Data Studio course, you will be awarded a CPD certificate as proof of your proficiency in Google Data Studio. Course Curriculum 1 sections • 4 lectures • 02:41:00 total length •Module 01: Introduction to GDS: 00:36:00 •Module 02: Data Visualization: 01:29:00 •Module 03: Geo-visualization: 00:16:00 •Module 04: A Socio-Economic Case Study: 00:20:00

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

Quick Data Science Approach from Scratch is an innovatively structured course designed to introduce learners to the fascinating world of data science. The course commences with an enlightening introduction, setting the stage for a deep dive into the essence and significance of data science in the modern era. Learners are guided through a landscape of insights, where misconceptions about data science are addressed and clarified, paving the way for a clear and accurate understanding of the field. In the second section, the course shifts its focus to pivotal data science concepts. Beginning with an exploration of data types and variables, learners gain a solid foundation in handling various data formats. The journey then leads to mastering descriptive analysis, a critical skill for interpreting and understanding data trends. Learners will also navigate through the intricate processes of data cleaning and feature engineering, essential skills for refining and optimizing data for analysis. The concept of 'Data Thinking Development' is introduced, fostering a mindset that is crucial for effective data science practice. The final section offers an immersive experience in applying these skills to a real-world scenario. Here, learners engage in defining a problem, choosing suitable algorithms, and developing predictive models. This practical application is designed to cement the theoretical knowledge acquired and enhance problem-solving skills in data science. Learning Outcomes Build a foundational understanding of data science and its practical relevance. Develop proficiency in managing various data types and conducting descriptive analysis. Learn and implement effective data cleaning and feature engineering techniques. Cultivate a 'data thinking' approach for insightful data analysis. Apply data science methodologies to real-life problems using algorithmic and predictive techniques. Why choose this Quick Data Science Approach from Scratch 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 Quick Data Science Approach from Scratch course for? Novices aiming to enter the data science field. Sector professionals integrating data science into their expertise. Academicians and learners incorporating data science in academic pursuits. Business strategists utilizing data science for enhanced decision-making. Statisticians and analysts broadening their expertise into the data science domain. Career path Entry-Level Data Scientist: £25,000 - £40,000 Beginner Data Analyst: £22,000 - £35,000 Emerging Business Intelligence Specialist: £28,000 - £45,000 Data-Focused Research Scientist: £30,000 - £50,000 Novice Machine Learning Practitioner: £32,000 - £55,000 Data System Developer (Starter): £26,000 - £42,000 Prerequisites This Quick Data Science Approach from Scratch does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Quick Data Science Approach from Scratch 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. Course Curriculum Section 01: Course Overview & Introduction to Data Science 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 Section 02: Data Science Concepts 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 Section 03: A Real Life Problem Problem Definition 00:05:00 Algorithms 00:14:00 Prediction 00:03:00 Learning Methods 00:05:00 Assignment Assignment - Quick Data Science Approach from Scratch 00:00:00

Using Data to Delight My BHAG or big hairy audacious goal is to make citizens delighted with government again by using this data and telling a story with analytics to show with facts what is happening, and being transparent in doing so. We are all citizens; we all have the ability to interact in this ecosystem. The time is now to make our communities better. I hope you will join me in learning about data coming in at record rates and how it can be used in your communities. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

Building and Scaling a Data Science Culture As your data and AI teams scale from one to thousands of employees, you will encounter roadblocks along the way. From handling messy data to productionization and customer adoption, these obstacles can delay or even derail otherwise strong teams. Drawing on experiences gleaned from hundreds of clients, Michael Li presents a framework that successful companies have embraced to build and scale their data teams. The talk goes over how organizations progress along three maturity curves: Analytical, Operational, and Organizational. As enterprises strive to move along each of these maturity curves, they must solve various organizational challenges and develop new capabilities and skills in order to become data-driven organizations. We will provide key takeaways for managers and executives for each step of the maturity curves. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Building and Scaling a Data Science Culture As your data and AI teams scale from one to thousands of employees, you will encounter roadblocks along the way. From handling messy data to productionization and customer adoption, these obstacles can delay or even derail otherwise strong teams. Drawing on experiences gleaned from hundreds of clients, Michael Li presents a framework that successful companies have embraced to build and scale their data teams. The talk goes over how organizations progress along three maturity curves: Analytical, Operational, and Organizational. As enterprises strive to move along each of these maturity curves, they must solve various organizational challenges and develop new capabilities and skills in order to become data-driven organizations. We will provide key takeaways for managers and executives for each step of the maturity curves. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Building Data Science Products? Think Business First Modern machine learning libraries are both a blessing and a curse. Due to the ease with which the libraries can be used, most users (newbies and practitioners alike) focus too much on tools and techniques. We will discuss the high-level thinking process of coming up with a machine learning algorithm by asking a business question before even thinking about the tools or technologies.Learning Objectives We will discuss the high-level thinking process of coming up with a machine learning algorithm by asking a business question before even thinking about the tools or technologies. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Everywhere, from tiny businesses to major corporations, needs people skilled in SQL. In light of this, our online training course has been developed to help you succeed by equipping you with all the necessary skills. The importance of mastering SQL increases if you're looking for your first job in the data industry. You will learn about topics such as SQL fundamentals, data wrangling, SQL analysis, AB testing, distributed computing with Apache Spark, Delta Lake, and more through four increasingly more challenging SQL projects with data science applications. These subjects will equip you with the skills necessary to use SQL creatively for data analysis and exploration, write queries quickly, produce datasets for data analysis, conduct feature engineering, integrate SQL with other data analysis and machine learning toolsets, and work with unstructured data. This Specialisation is designed for a learner with little or no prior coding expertise who wants to become proficient with SQL queries. Experts have meticulously planned out the curriculum for the SQL Skills Training course with years of expertise. As a result, you will find it simple to learn the course material. Learning outcome After finishing the course, you'll Learn to utilise the tools for view creation Become familiar with updating columns and indexed views Be able to test and debug Be able to search a database using SQL Become more familiar with inline table-valued functions Learn the fundamentals of transactions and multiple statements Why Prefer US? Opportunity to earn a certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Standards-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** SQL Programming Course Module 01: Course Introduction Introduction Course Curriculum Overview Overview of Databases Module 02: SQL Environment Setup MySQL Installation MySQL Workbench Installation Connecting to MySQL using Console Module 03: SQL Statement Basics Overview of Challenges SQL Statement Basic SELECT Statement SELECT DISTINCT Column AS Statement COUNT built-in Method usage SELECT WHERE Clause - Part One SELECT WHERE Clause - Part Two Statement Basic Limit Clause Statement Using BETWEEN with Same Column Data How to Apply IN Operator Wildcard Characters with LIKE and ILIKE Module 04: GROUP BY Statements Overview of GROUP BY Aggregation function SUM() Aggregation MIN() and MAX() GROUP BY - One GROUP BY - Two HAVING Clause Module 05: JOINS Overview of JOINS Introduction to JOINS AS Statement table INNER Joins FULL Outer Join LEFT Outer JOIN RIGHT JOIN Union Module 06: Advanced SQL Commands / Statements Timestamps EXTRACT from timestamp Mathematical Functions String Functions SUBQUERY Module 07: Creating Database and Tables Basic of Database and Tables Data Types Primary key and Foreign key Create Table in SQL Script Insert Update Delete Alter Table Drop-Table NOT NULL Constraint UNIQUE Constraint Module 08: Databases and Tables Creating a Database backup 10a Overview of Databases and Tables 10c Restoring a Database CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The course can be helpful for anyone working in the SQL fields, whether self-employed or employed, regardless of their career level. Requirements You will not need any prior background or expertise to enrol in this course. Career path The vocation of SQL Skills Training moves very quickly but pays well. This position provides unparalleled satisfaction. This is your opportunity to learn more and start changing things. Query Language Developer Server Database Manager Python Developer Technical Consultant Project Implementation Manager Software Developer (SQL) Certificates Certificate of completion Digital certificate - £10

Becoming a Data Quality Expert Data science is an exploding field with tremendous demand. Having high quality data is an absolute must for any business today and data informs every decision a business must make. But what if you have poor quality data? What if your company acquired another company and the data structure does not match? What if you have large gaps in the data you have vs. what you need?Imagine yourself as an IT project/program manager who has run many engagements for the business. You have great PM skills and you run your agenda with the precision of a Swiss watch. But you now have to run Data Quality for your organization. Can you just program manage this and be fine? What will be different about this than any other IT project?Wake-up call: a WHOLE LOT! You must acquire a lot of new skills and you must become a data expert as quickly as possible. I want to share with you my journey and experience. I have had to go from deeply technical in some IT areas, to project/program managing general IT projects, to gaining specialized skills in data quality. I will share with you my assessment, gap analysis and mitigation strategy that transformed me into a data quality expert.