5482 Sciences courses

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

Overview Dive deep into the mesmerising world of particle physics with our comprehensive course titled 'Particle Physics'. Ever pondered the question, 'what is particle physics?' or been intrigued by the standard model of particle physics? This course unravels the mysteries of the universe, starting from the tiniest elementary particles to the vast complexities of nuclear physics. Transitioning from one module to the next, learners will be captivated by the intricacies of particle accelerators and the marvels of radiation detectors. By the culmination of this course, the standard model of particle physics will no longer be an enigma but a fascinating realm of knowledge you've mastered. Learning Outcomes: Understand the foundational concepts and significance of particle physics. Identify and differentiate between various elementary particles. Gain insights into the structure and properties of the nucleus. Delve into the principles and applications of nuclear physics. Comprehend the workings and importance of particle accelerators. Acquire knowledge on radiation detectors and their pivotal role in research. Grasp the intricacies and concepts behind the standard model of particle physics. Why buy this Particle Physics? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Particle Physics there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Particle Physics is suitable for:  Individuals with a keen interest in understanding the universe at a microscopic level. Science students aiming to expand their knowledge in advanced physics topics. Teachers and lecturers seeking to update their curriculum with the latest in particle physics. Researchers in the field of physics looking for a comprehensive refresher course. Enthusiasts eager to delve into the complexities of the universe's building blocks. Prerequisites This Particle Physics 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. Career path Particle Physicist: Average salary range £50,000 - £70,000 Annually Nuclear Engineer: Average salary range £40,000 - £60,000 Annually Radiation Specialist: Average salary range £45,000 - £65,000 Annually Research Scientist (Physics): Average salary range £35,000 - £55,000 Annually Accelerator Operator: Average salary range £30,000 - £50,000 Annually Physics Lecturer: Average salary range £40,000 - £60,000 Annually Course Curriculum Module-01: Introduction to Particle Physics Introduction to Particle Physics 00:22:00 Module-02: Elementary Particles Elementary Particles 00:20:00 Module-03: The Nucleus The Nucleus 00:23:00 Module-04: Nuclear Physics Nuclear Physics 00:18:00 Module-05: Particle Accelerators Particle Accelerators 00:23:00 Module-06: Radiation detectors Radiation Detectors 00:37:00 Module-07: The Standard Model The Standard Model 00:15:00 Assignment Assignment - Particle Physics 00:00:00

Embark on a journey beneath the waves with the 'Basics of Marine Archaeology Diploma'. Navigate through the enigmatic world of underwater history, where the oceans reveal sunken secrets and hidden tales of bygone eras. From the alluring mysteries of shipwrecks to the silent stories of submerged settlements, this course invites you to decode the enthralling narrative of our maritime past. Module by module, immerse yourself into a profound educational abyss, exploring tools, methodologies, and the diverse array of underwater sites that punctuate our ocean floors. Not only will your intellect be piqued, but your ethical and legal discernment will also be sharpened, ensuring your expeditions into the depths are both responsible and respectful to our submerged heritage. Learning Outcomes Analyse and comprehend varied underwater archaeological sites and their historical significance. Employ appropriate archaeological tools and innovative techniques effectively in maritime explorations. Understand and adhere to legal and ethical protocols in marine archaeological practice. Apprehend and apply advanced technological methodologies in underwater excavations. Foresee and engage with current trends and emerging prospects in the field of marine archaeology. Why buy this Basics of Marine Archaeology Diploma? 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 Basics of Marine Archaeology Diploma for? Individuals passionate about maritime history and underwater explorations. Students of archaeology seeking to diversify their academic knowledge. Hobbyists interested in understanding the realm of underwater archaeological sites. Professionals in the field of history or archaeology looking to specialise in a unique domain. Environmentalists aiming to blend knowledge of oceanography with archaeological practices. Career path Marine Archaeologist: £28,000 - £45,000 Underwater Photographer: £20,000 - £40,000 Maritime Historian: £25,000 - £45,000 Conservation Specialist: £22,000 - £37,000 Museum Curator with a marine specialty: £23,000 - £40,000 Archaeological Illustrator: £18,000 - £30,000 Prerequisites This Basics of Marine Archaeology Diploma does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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 Module 01: Introduction to Marine Archaeology Introduction to Marine Archaeology 00:14:00 Module 02: Tools and Techniques Tools and Techniques 00:13:00 Module 03: Types of Underwater Sites Types of Underwater Sites 00:15:00 Module 04: Prehistoric Marine Archaeology Prehistoric Marine Archaeology 00:11:00 Module 05: Legal and Ethical Considerations Legal and Ethical Considerations 00:09:00 Module 06: Advanced Technologies in Marine Archaeology Advanced Technologies in Marine Archaeology 00:11:00 Module 07: Current Trends and Future Prospects Current Trends and Future Prospects 00:08:00

The 'Logistics of Crude Oil and Petroleum Products' course provides a comprehensive understanding of the various methods of transporting crude oil and petroleum products. From marine transport to pipeline operations and storage, learners will gain insights into the crucial logistics involved in the petroleum industry. Learning Outcomes: Identify the different methods of transporting crude oil and petroleum products. Understand the logistics and operations involved in marine transport and pipeline systems. Compare the costs associated with different transportation methods. Gain knowledge of storage and delivery processes to refineries. Learn about the dispatch of petroleum products and the controls implemented during the process. Why buy this Logistics of Crude Oil and Petroleum Products? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Logistics of Crude Oil and Petroleum Products there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Logistics of Crude Oil and Petroleum Products course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Logistics of Crude Oil and Petroleum Products does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Logistics of Crude Oil and Petroleum Products 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Logistics of Crude Oil and Petroleum Products is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: About The Course Learning objectives 00:04:00 Unit 02: The Different Methods of Transport Introduction to the different methods of transport 00:05:00 Unit 03: Marine Transport The different types of tankers 00:05:00 The different types of charters 00:02:00 The cost of marine transport 00:04:00 Prices and costs of marine transport 00:05:00 Prices and costs of marine transport 00:05:00 Regulations : National flag requirement 00:01:00 Flags of convenience 00:01:00 Operating aspects 00:04:00 Controls on loading 00:07:00 Administrative formalities 00:01:00 The reception of tankers 00:07:00 Unit 04: Transport by Pipeline The constraints 00:05:00 The cost of transport by pipeline 00:03:00 Unit 05: Comparing Transport Costs Comparing transport costs 00:06:00 Unit 06: Storage and Delivery to the Refinery Storage and delivery to the refinery 00:03:00 Unit 07: Dispatch of Petroleum Products Introduction 00:03:00 Dispatch by pipeline 00:07:00 Dispatch by water 00:07:00 Dispatch by rail 00:06:00 Dispatch by road 00:05:00 Unit 08: Controls at Dispatch Quality 00:02:00 Quantities 00:02:00 Administrative accounting methods 00:01:00 Customs formalities 00:02:00 Assignment Assignment - Logistics of Crude Oil and Petroleum Products 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science 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 R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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 Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Embark on a mathematical journey with our Functional Skills Maths course, designed to transform numbers and equations from daunting puzzles into fascinating challenges. Imagine standing at the crossroads of comprehension and mastery, where every integer and decimal is a stepping stone towards success. Our curriculum elegantly weaves through topics like the enigmatic world of integers, the rhythmic dance of factors and multiples, and the delicate balance of fractions. Explore the wonders of BODMAS, a simplification rule that brings order to chaos. Delve into the depths of decimal numbers and rational numbers, where precision meets practicality. Experience the thrill of approximation, and the precision of estimation and scientific notation, as you navigate through the practical realms of percentages, ratios, proportions, and the unitary method. Finally, grapple with real-world scenarios involving profit, loss, discount, and tax - the very essence of everyday maths. As you progress, each module unfolds like a chapter of a grand narrative, revealing the beauty and logic of mathematics. Whether you're deciphering the secrets of percentages or unraveling the complexities of ratio and proportion, this course promises a transformative experience. By turning abstract concepts into tangible skills, you'll not only gain knowledge but also the confidence to apply it in various contexts. Get ready to embark on a journey that not only educates but also empowers, as we guide you through the magical world of functional maths. Learning Outcomes Develop a robust understanding of key mathematical concepts including integers, fractions, and decimals. Master the BODMAS rule for effective problem-solving in mathematical equations. Gain proficiency in applying mathematical principles to real-life scenarios involving profit, loss, and taxation. Acquire skills in approximation, estimation, and understanding scientific notation for practical applications. Enhance ability to calculate and manipulate percentages, ratios, and proportions for diverse mathematical challenges. Why choose this Functional Skills Maths course? Individuals seeking to solidify their foundational maths skills. Students preparing for advanced studies in mathematics or related fields. Professionals requiring enhanced numerical skills for workplace applications. Anyone interested in improving their problem-solving and analytical abilities. Learners aspiring to apply mathematical concepts in everyday life. Who is this Functional Skills Maths course for? Individuals keen on mastering freestyle swimming. Beginners aiming to understand swimming basics and techniques. Athletes looking to enhance their swimming performance. Fitness enthusiasts seeking a comprehensive water workout. Adventurers aiming for open water swims or triathlon participation. Career path Financial Analyst: £30,000 - £50,000 Data Scientist: £35,000 - £70,000 Accountant: £25,000 - £50,000 Actuary: £32,000 - £60,000 Market Research Analyst: £24,000 - £45,000 Operational Researcher: £27,000 - £40,000 Prerequisites This Functional Skills Maths does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Functional Skills Maths 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 Integers ( Directed Numbers) Lecture 1 Introduction 00:02:00 Lecture 2 Multiplying any digit number by 11, 22, and 33 00:09:00 Lecture 3 Integers and ordering of integers 00:06:00 Lecture 4 Addition and Subtractions of Integers 00:07:00 Lecture 5 Operations on Integers 00:04:00 Lecture 6 Multiplication and Division of Integers 00:04:00 Lecture 7 Powers of Integers (Exponents) 00:04:00 Factors and Multiples Lecture 8 Complete knowledge about factors and multiples 00:06:00 Lecture 9 Divisibility tests for 2,3,4,5,6 00:07:00 Lecture 10 Divisibility rules 7,8,9,10,11 00:06:00 Lecture 11 Prime Factorization 00:06:00 Lecture 12 Highest Common Factor HCF 00:10:00 Lecture 13 Least Common Multiple LCM 00:16:00 Lecture 14 Relation between LCM and HCF 00:04:00 Fractions Lecture 15 Classification of Fractions 00:04:00 Lecture 16 Convert mixed to improper and improper to mixed fractions 00:03:00 Lecture 17 Equivalent Fractions 00:04:00 Lecture 18 Comparing Fractions after converting to like fractions 00:09:00 Lecture 19 Reducing a fraction to lowest term 00:04:00 Lecture 20 Addition and subtraction OF fractions 00:08:00 Lecture 21 Multiplication and division of fractions 00:11:00 Lecture 22 Word problems on fractions 00:16:00 Simplification Rule : BODMAS Lecture 23 BODMAS and rules to remove brackets 00:03:00 Lecture 24 Simplify expressions using BODMAS rules 00:05:00 Lecture 25 Simplify expressions involving fractions using BODMAS 00:07:00 Decimal numbers Lecture 26 Decimal numbers in relation to fractions 00:08:00 Lecture 27 Like and unlike Decimals 00:05:00 Lecture 28 Ordering of Decimal numbers 00:10:00 Lecture 29 Addition and subtraction of Decimal 00:07:00 Lecture 30 Multiplication of Decimal 00:03:00 Lecture 31 Division of Decimal 00:05:00 Rational Numbers Lecture 32 Rational number 00:02:00 Lecture 33 Representation of Rational Numbers on Number line 00:04:00 Lecture 34 Determining which fraction is terminating or non terminating 00:05:00 Lecture 35 shortcut method of writing decimal expansion of fraction to decimal 00:08:00 Approximation Lecture 36 Rounding to whole number 00:06:00 Lecture 37 Rounding to required number of decimals (1 d.p. ) 00:05:00 Lecture 38 rounding to significant digits 00:07:00 Lecture 39 Practice question on three methods of approximation 00:05:00 Estimation and Scientific Notation or Standard form Lecture 40 Estimation 00:05:00 Lecture 41 Scientific Notation 00:07:00 Lecture 42 Operation on numbers when they are in scientific notation 00:06:00 Percentage Lecture 43 Percentage to fraction and fraction to percentage 00:06:00 Lecture 44 Percentage of a quantity and conversation to decimal 00:06:00 Lecture 45 Expressing one quantity as percentage of another quantity 00:06:00 Lecture 46 Finding increase decrease percent 00:05:00 Lecture 47 Uses of percentages-Word Problems 00:09:00 Ratio and Proportion Lecture 48 Ratio- How to express as simple ratio 00:09:00 Lecture 49 How to compare Ratios 00:04:00 Lecture 50 Word problems on finding ratios 00:07:00 Lecture 51To divide a given quantity into a given Ratio 00:11:00 Lecture 52 Proportion 00:04:00 Lecture 53 Practice problems on Proportion 00:06:00 Lecture 54 Continued proportion 00:06:00 Unitary Method and its Applications Lecture 55 Direct Variation ( or proportion) 00:04:00 Lecture 56 Problems based on Direct proportion 00:10:00 Lecture 57 Inverse Variation ( or proportion) 00:10:00 Lecture 58 Multiple Ratios 00:10:00 Profit , Loss, discount and Tax Lecture 59 Basics - Profit and Loss 00:04:00 Lecture 60 More practice problems on Profit & Loss 00:06:00 Lecture 61 Selling price formula and Problems 00:04:00 Lecture 62 Cost price formula and Problems 00:03:00 Lecture 63 Higher problems on Profit and Loss 00:08:00 Lecture 64 Basics - Discount.mp4 00:05:00 Lecture 65 Practice problems on Discount 00:04:00 Lecture 66 Tax 00:06:00 Mock Exam Mock Exam - Functional Skills Maths 00:20:00 Final Exam Final Exam - Functional Skills Maths 00:20:00

Dive deep into the electrifying realm of electrical power systems and high-voltage engineering. 'Electrical Power System and High Voltage Engineering' paves the way for enthusiasts to harness the power of cutting-edge electrical innovations. Through eight meticulously structured modules, learners get an intricate glimpse into the diverse types of high voltage, their generation, and the nuances of AC and DC voltages. As you delve deeper, you're not just gaining insights; you're powering your potential in a high-voltage sector. Learning Outcomes Grasp foundational concepts of the electrical power system and high voltage. Differentiate among the various types of high voltage. Understand the processes involved in generating high-voltage AC at different frequencies. Acquire knowledge on impulse high voltage generation. Gain proficiency in the techniques of high-voltage DC generation. Why choose this Electrical Power System and High Voltage Engineering course? 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 Electrical Power System and High Voltage Engineering 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 Electrical Power System and High Voltage Engineering course for? Engineering students keen on specialising in power systems. Electrical engineers looking to upgrade their knowledge. Professionals in the power sector aiming for deeper insights. Technical consultants in the energy domain. Innovators eager to understand the intricacies of high voltage engineering. Career path Power System Engineer: £35,000 - £60,000 High Voltage Engineer: £40,000 - £65,000 Electrical Design Engineer: £30,000 - £55,000 Technical Project Manager in Power Systems: £45,000 - £70,000 Transmission Line Engineer: £38,000 - £63,000 Power System Analyst: £37,000 - £61,000 Prerequisites This Electrical Power System and High Voltage Engineering does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Electrical Power System and High Voltage Engineering 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 Electrical Power System and High Voltage Engineering Module 1- Introduction to Electrical Power System and High Voltage 00:25:00 Module 2- Types of High Voltage 00:17:00 Module 3- Generation of High Voltage AC at Power Frequency 00:30:00 Module 4- Generation of High Voltage High Frequency AC 00:14:00 Module 5- Generation of High Voltage Impulse Part 1 00:37:00 Module 6- Generation of High Voltage Impulse Part 2 00:14:00 Module 7- Generation of High Voltage DC Part 1 00:43:00 Module 8- Generation of High Voltage DC Part 2 00:45:00

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

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Data Science & Machine Learning with R from A-Z there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z 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. Career path Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Getting Started with R Getting Started 00:11:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Assignment Assignment - Data Science & Machine Learning with R 00:00:00

Dive into the intriguing world of food with the 'Food Technology Diploma Level 3'. This course takes you on a journey from the foundational aspects of food technology to the intricacies of food chemistry, biotechnology, and microbiology. With modules dedicated to food processing techniques and the ever-important topic of food packaging and sustainability, learners will acquire a holistic understanding of the subject. Embark on a learning experience that not only equips you with the knowledge of food technology but also imparts a consciousness about sustainable practices. Learning Outcomes Understand the basic concepts and importance of food technology in modern society. Gain insights into the role of chemistry, biotechnology, and microbiology in food production. Develop proficiency in varied food processing techniques and their applications. Comprehend the significance of sustainable food packaging and its impact on the environment. Attain a comprehensive perspective on the relationship between food technology and sustainability. Why buy this Food Technology Diploma Level 3? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Food Technology Diploma Level 3 there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Food Technology Diploma Level 3 for? Individuals passionate about the food industry and technological advancements. Those keen on understanding the science behind food production. Aspiring food technologists aiming to enhance their qualifications. Professionals in the food industry looking to broaden their knowledge base. Sustainability advocates wishing to delve deeper into eco-friendly food practices. Prerequisites This Food Technology Diploma Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Food Technology Diploma 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. Career path Food Technologist: £25,000 - £35,000 Food Quality Control Analyst: £22,000 - £30,000 Food Production Manager: £30,000 - £45,000 Food Microbiologist: £24,000 - £34,000 Sustainability Consultant (Food Industry): £28,000 - £40,000 Food Packaging Specialist: £27,000 - £37,000 Course Curriculum Module 01: Introduction to Food Technology Introduction to Food Technology 00:14:00 Module 02: Food Chemistry Food Chemistry 00:15:00 Module 03: Food Biotechnology Food Biotechnology 00:11:00 Module 04: Food Microbiology Food Microbiology 00:14:00 Module 05: Food Processing Techniques Part-1 Food Processing Techniques Part-1 00:15:00 Module 06: Food Processing Techniques Part-2 Food Processing Techniques Part-2 00:15:00 Module 07: Food Packaging and Sustainability Food Packaging and Sustainability 00:13:00