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Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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 £85 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 Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Reduce Stress - Meditation and Visualisation Certification Figuring out how to decrease pressure utilizing reflection and perception is significant for everybody today. As the speed of present day life increments, so does our pressure, and figuring out how to manage it appropriately makes you more joyful and more profitable. This course gives a complete knowledge into both the reflection and perception methods you need, to lessen your feelings of anxiety; why they work, how they work and, in particular, how you can utilize them for your potential benefit. From the full definition and advantages of perception and reflection to incredible methods for you to accomplish full unwinding, this course covers all you require to think about lessening pressure through contemplation and representation. You will Learn The full definitions and advantages of both representation and contemplation; Successful thoughtful procedures and styles to assist you with lessening pressure; Step by step instructions to effectively utilize perception to accomplish unwinding; Step by step instructions to outfit the de-focusing on force of Mettā Meditation, which joins contemplation and representation; Every one of the means you need to take, to effectively utilize reflection and representation, to lessen pressure. Advantages of taking this Course You will actually want to deal with a distressing circumstance; You will improve your connections at home and at work; You will figure out how to be more beneficial, because of managing pressure; You will figure out how to apply incredible and flexible reflection and representation procedures; You will be more joyful, more loose and totally settled in your life;

Advanced Kibana training course description This training course is aimed at users who already have some experience with Kibana, who are looking to further their knowledge. What will you learn Lens Timelion Maps Custom Visualisations with Vega Canvas Filters and Controls Drilldown and Dashboards KQSL and ElasticQueries Scripted and RunTime Fields Alerts and Alarms Advanced Kibana training course details Who will benefit: Users who already have some experience with Kibana, who are looking to further their knowledge. Prerequisites: None Duration 1 day Advanced Kibana training course contents Topics Lens Visualisation types (tables,bars,charts) Category breakdown Adding multiple metrics Using formulas in metrics Labels Adding reference layer Limitations Visualise Library Timeseries, Metrics Different types of aggregations Maps GeoMapping Heat Maps Using ES index as data source Visualisation, tool tips Custom Visualisations with Vega Introduction to vega scripting Canvas Widgets and Texts Elasticsearch SQL Canvas Expressions Filters and Controls Dropdown filters Ad-hoc filters Searchbar filters Drilldown Dashboards Linking one dashboard to another KQSL and ElasticQueries Bool Query AND/OR Phrase Part match vs keyword search Wildcard search Scripted and RunTime Fields Creating ad-hoc calculated fields using scripts Performance issues Alerts and Alarms Query Based Formatting output Connector types(email,index,teams etc)

Data dashboards provide key information to stakeholders so that they can make informed decisions. While there are plenty of software solutions for building these essential data products, there is much less guidance on how to design dashboards to meet the diverse needs of users.  This course is for anyone who is building or implementing dashboards, and wants to know more about design principles and best practice. You could be using business intelligence software (such as Power BI or Tableau), or implementing bespoke solutions.  The course will give your team the ability to evaluate user needs and levels of understanding, make informed decisions about chart selections, and make effective use of interactivity dynamic data.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve.  Sample learning content  Session 1: Data with a purpose Understanding the different types of dashboard. Information overload and other common dashboard pitfalls. Assessing user needs and levels of data fluency. Session 2: Planning a dashboard Assessing diverse user needs and levels of data fluency. Taking a User Experience (UX) approach to design and navigation. Applying an interative and collaborative approach to onboarding. Session 3: Graphs, charts and dials  Understanding how graphical perception informs chart choices. Making intelligent design choices to help users explore. Design principles for layout and navigation. Session 4: Using interactivity  Making effective use of filters to slice and dice data sets. Using layers of information to enable drilldown data exploration. Complenting dashboards with automated alerts and queries. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial “Alan was great to work with, he took us through the concepts behind data visualisation which means our team is now equipped for the future. He has a wide range of experience across the topic that is delivered in a clear, concise and friendly manner. We look forward to working with Alan again in the future.” John Masterson | Chief Product Officer | ImproveWell

Data has become the most important resource for every organisation – but the insights gained from data analysis will only ever be truly valuable if they can be clearly expressed to other people.  This course is for anybody who works with data, and needs to communicate the meaning that's in the numbers to colleagues, customers, bosses or external stakeholders.  It will give you or your team the confidence and skills to translate raw data into compelling visual stories for your key audiences. The principles and skills covered apply to the simplest PowerPoint chart, to more complex interactive visualisations.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve.  Sample learning content Session 1: What makes a great data-driven story The key elements of a successful infographic or presentation. Industry best practice, and discussion of good (and bad) examples. A simple framework for identifying the Audience, Story and Action. Session 2: Data in context How to balance function and aesthetic appeal. Identifying the right graph, chart, infographic or other visual. Framing the data and providing contextual information. Session 3: Designing for the human brain Using colours to add emphasis and meaning. Design and layout principles, and creating hierarchies of information. The principle of ‘self-sufficiency’, and removing clutter. Session 4: Navigation and narrative Tailoring visualisations for different types of communications. Structuring presentations and longer reports. Thinking in layers to create interactive dashboards. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets.
 Testimonial “I was familiar with Alan’s work as a Guardian Masterclass instructor on data visualisation and digital journalism, which made it easy for me to recommend him for onsite training at the Liverpool School of Tropical Medicine. We had a large group of people interested in honing their abilities to depict their research and stories in engaging ways. Alan’s course provided great insight about common communication pitfalls and how to avoid them, how to become better communicators by understanding the audience diversity, and it showcased some great online tools for creating infographics. This should be mandatory training for all students, academics, report writers and those involved with conveying research to the media as it will help increase the clarity and accessibility of our own research stories.”
 Dr Lee Haines | Liverpool School of Tropical Medicine

***24 Hour Limited Time Flash Sale*** Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Immerse yourself in the world of Data Science, Machine Learning and Python with our exclusive bundle! Presenting eight thoughtfully curated courses, this bundle aims to enhance your understanding of intricate concepts. Within this collection, we proudly offer three QLS-endorsed courses: "2021 Data Science & Machine Learning with R from A-Z", "Excel Pivot Tables, Pivot Charts, Slicers, and Timelines", and "Machine Learning with Python", each complemented by a hardcopy certificate upon completion. Additionally, delve deeper with our five relevant CPD QS accredited courses. Explore Python Data Science with Numpy, Pandas, and Matplotlib. Uncover the secrets of R Programming for Data Science, enhance your statistical prowess with Statistics & Probability for Data Science & Machine Learning, and master spatial visualisation in Python. To top it all, there's a course on Google Data Studio for Data Analytics. Key Features of the Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Bundle: 3 QLS-Endorsed Courses: We proudly offer 3 QLS-endorsed courses within our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python bundle, providing you with industry-recognized qualifications. Plus, you'll receive a free hardcopy certificate for each of these courses. QLS Course 01: 2021 Data Science & Machine Learning with R from A-Z QLS Course 02: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines QLS Course 03: Machine Learning with Python 5 CPD QS Accredited Courses: Additionally, our bundle includes 5 relevant CPD QS accredited courses, ensuring that you stay up-to-date with the latest industry standards and practices. Course 01: Python Data Science with Numpy, Pandas and Matplotlib Course 02: R Programming for Data Science Course 03: Statistics & Probability for Data Science & Machine Learning Course 04: Spatial Data Visualisation and Machine Learning in Python Course 05: Google Data Studio: Data Analytics In Addition, you'll get Five Career Boosting Courses absolutely FREE with this Bundle. Course 01: Professional CV Writing Course 02: Job Search Skills Course 03: Self-Esteem & Confidence Building Course 04: Professional Diploma in Stress Management Course 05: Complete Communication Skills Master Class Convenient Online Learning: Our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python courses are accessible online, allowing you to learn at your own pace and from the comfort of your own home. Learning Outcomes: Master the usage of Excel Pivot Tables, Pivot Charts, Slicers, and Timelines. Develop proficiency in Machine Learning using Python. Acquire skills to manipulate data using Numpy, Pandas, and Matplotlib. Learn to code in R for Data Science applications. Understand the application of Statistics & Probability in Data Science & Machine Learning. Learn to create impactful data visualisations and analyse data using Google Data Studio. The "Data Science & Machine Learning, Excel Pivot & Machine Learning with Python" bundle is a comprehensive compilation designed to equip you with the theoretical knowledge necessary for the fast-evolving data-driven world. The three QLS-endorsed courses provide foundational understanding in Data Science, Machine Learning with R, Excel Pivot functionalities, and Machine Learning with Python, thereby setting a strong base. Furthermore, the five CPD QS accredited courses offer a deeper dive into the world of Data Science. Whether it is harnessing Python's power for data science tasks, exploring R programming, mastering statistical techniques, understanding spatial data visualisation in Python, or learning to navigate Google Data Studio for Data Analytics, this bundle has you covered. With this comprehensive learning experience, gain the theoretical insight needed to navigate and succeed in the dynamic field of data science. CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals interested in theoretical concepts of Data Science and Machine Learning. Professionals looking to enhance their knowledge in Excel Pivot Tables and Charts. Aspiring data scientists who want to learn Python and R programming for data science. Anyone seeking to understand data visualisation and analytics through Python and Google Data Studio. Career path Data Scientist: Leveraging data for actionable insights (£40,000 - £90,000 per annum). Machine Learning Engineer: Designing and implementing machine learning systems (£50,000 - £90,000 per annum). Excel Analyst: Using Excel for data analysis and visualisation (£30,000 - £60,000 per annum). Python Developer: Developing applications using Python (£40,000 - £80,000 per annum). Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost

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

Data Is The Language Of The Powerholders | Designed By Industry Specialists | Level 7 QLS Endorsed Career Objective Driven Data Science Courses | 10 QLS Endorsed Hard Copy Certificates Included | Lifetime Access | Installment Payment | Tutor Support

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.