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Journalism is a noble and respective profession. Journalists bear the burden of presenting the crucial news and information to the mass people. If you want to build your career as a journalist or in the media industry, this journalism course can be the first step towards your professional journey. Learn the necessary skills you need to be a journalist from this Journalism course today. Our Journalism course lessons were prepared by experts and feature interactive activities. You'll learn how you can use various opportunities effectively from industry experts. This Journalism course has been divided into understandable and manageable sections that will help you grasp each concept- from the basic to advanced course components. Learn from industry experts today and enhance your skills and knowledge in no time. This Journalism course will increase your possibility to get your desired job and boost your personal growth. Learning Objectives Learn the basic principles of journalism Understand the roles and responsibilities of a journalist Familiarise with the ethical values and aspects of journalism Learn about various legal regulations and obligations Understand the language of journalism Be able to take notes fast and effectively Learn how to present your news attractively Grasp effective tips about data visualisation and presentation Who is this Course for? The Journalism course is ideal for highly aspiring individuals who wish to enhance their professional skills and train for the job they want! Also, this course is highly beneficial for people who want to have some in-depth knowledge on this topic and keep up to date with the latest information. So, you can enrol in this course if you are: Journalists Reporters Editors News Presenters News Researchers Study the Journalism course today and enhance your professional skillset from the comfort of your home! Entry Requirement There are no formal entry requirements for the Journalism course; with enrollment, this course is open to anyone! Anyone with a passion for learning about Journalism can enrol in this course without any hesitation. Although, the learner should be aged 16 or over to enrol in this course. Also, they need to have a good understanding of the English language to attend this course and understand what this course is about. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £4.99 and the hard copy for £9.99. Also, you can order both PDF and hardcopy certificates for £12.99. Career path This Journalism course will help you gain all the necessary theoretical knowledge to excel in the relevant field. Enrol on our Journalism course now and get started on the journey of taking your career to the next level. Course Curriculum Module 01: Introduction and Principles of Journalism Introduction and Principles of Journalism 00:18:00 Module 02: History and Development of Journalism History and Development of Newspaper Journalism 00:26:00 Module 03: Interviewing Interviewing 00:35:00 Module 04: Newspaper Journalism Newspaper Journalism 00:30:00 Module 05: News Writing, Production and Reporting News Writing, Production and Reporting 00:20:00 Module 06: Television Journalism Television Journalism 00:32:00 Module 07: Radio Journalism Radio Journalism 00:37:00 Module 08: Media Regulatory Bodies Media Regulatory Bodies 00:31:00 Module 09: Writing Skills for Journalists Writing Skills for Journalists 00:41:00 Module 10: Journalism law Journalism Law 00:35:00 Module 11: Defamation Defamation 00:20:00 Module 12: Journalism Ethics Journalism Ethics 00:17:00 Module 13: Health and Safety for Journalists Health and Safety for Journalists 00:38:00 Module 14: Niche Journalism Niche Journalism 00:24:00 Module 15: Tips on Writing a Good Feature Story Tips on Writing a Good Feature Story 00:34:00 Module 16: Online and Freelance Journalism Online and Freelance Journalism 00:16:00 Module 17: Becoming a Journalist Becoming a Journalist 00:29:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Step into the riveting realm of Solidworks, where imagination meets precision, and ideas transform into tangible designs. 'Solidworks: Beginner to Advanced' is a meticulously crafted journey tailored for curious minds keen to master the art and science of this software. Embark on a voyage starting from a foundational understanding, glide through sketches, part modelling, and eventually delve into intricate assemblies, drawings, and captivating animations. By the culmination, you'll possess the prowess to bring your creative visions to life with unparalleled precision. Learning Outcomes Acquire proficiency in navigating and utilising the core functionalities of Solidworks. Transform rudimentary sketches into detailed and precise 3D models. Master advanced part modelling, assembly techniques, and drawing intricacies. Immerse in the world of appearances, scenes, and produce realistic renderings. Execute captivating animations that showcase dynamic design components. Why choose this Solidworks: Beginner to Advanced 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 Solidworks: Beginner to Advanced 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 Solidworks: Beginner to Advanced course for? Novices keen to explore the intricacies of Solidworks. Engineers looking to enhance their design capabilities. Product designers aspiring to elevate their 3D modelling skills. Architecture and design students keen on a comprehensive software learning experience. Industry professionals aiming to stay abreast of cutting-edge design tools. Career path CAD Designer: £25,000 - £35,000 Mechanical Engineer: £30,000 - £50,000 Product Design Engineer: £28,000 - £48,000 Solidworks Draughtsperson: £24,000 - £34,000 Design Manager: £40,000 - £60,000 3D Visualisation Artist: £23,000 - £40,000 Prerequisites This Solidworks: Beginner to Advanced does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Solidworks: Beginner to Advanced 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 Introduction About the course 00:02:00 Course concept 00:01:00 Getting to Know Solidworks Creating a New Document 00:01:00 User Interface 00:02:00 Mouse Movements - Sketch 00:02:00 Mouse Movements - Part 00:03:00 Sketch Creating a Sketch Document 00:02:00 Basic Sketch Tools 00:07:00 Dimensions and Relations 00:12:00 Mirror Entities 00:02:00 Linear and Circular Sketch Pattern 00:06:00 Units 00:02:00 Sketch to Part Conversion 00:03:00 Opening/Saving Part Document 00:01:00 Part Modeling Basics Extruded Boss Base 00:03:00 Extruded Boss Base Additional 00:04:00 Extruded Cut 00:03:00 Sketch on the Part 00:02:00 Sketch on the New Plane 00:05:00 Draft 00:03:00 Shell 00:02:00 Fillet and Chamfer 00:03:00 Convert and Offset Entities 00:02:00 Lofted Boss 00:03:00 Revolved Boss 00:02:00 Swept Boss 00:05:00 Part and Sketch Modification 00:02:00 Part Modeling Advanced 3D Sketch 00:03:00 Density and Material 00:02:00 Measuring Tools 00:03:00 Linked Dimensions 00:04:00 Equations 00:05:00 Mirror 00:03:00 Hole Wizard 00:03:00 Reference Geometry 00:03:00 Feature Scope 00:02:00 Configurations And Design Table Creating a Design Table 00:06:00 Adding Configurations 00:05:00 Assembly Basics Inserting Part Relative to the Origin 00:02:00 Inserting Parts Relative to Planes 00:02:00 Standard Mates 00:04:00 Move Components 00:02:00 Mirror Component 00:01:00 Assembly Advanced Distance and Angle 00:04:00 Profile Centre 00:04:00 Symmetry and Width 00:05:00 Path Mate 00:05:00 Linear Coupler 00:06:00 Collision Detection 00:02:00 Interference Detection 00:03:00 Assembly Features 00:02:00 Subassembly 00:03:00 Drawing Basics Creating a Drawing Sheet 00:01:00 Orthographic Views and Edit Sheet 00:04:00 Projected View and View Properties 00:02:00 Smart Dimension and Model Item 00:05:00 Saving Options 00:01:00 Relative to Model View 00:03:00 Section View 00:04:00 Auxiliary View 00:03:00 Detail View 00:02:00 Broken Out Section 00:02:00 Break View 00:02:00 Alternate Position View 00:02:00 View Focus 00:02:00 Drawing Advanced Bill of Materials (BOM) 00:03:00 Bom Sort 00:01:00 Missing Item in Bom 00:02:00 Custom Properties 00:02:00 Equations in Bom 00:03:00 Show/Hide Component 00:02:00 Linked Notes 00:02:00 Measuring Tool 00:02:00 Isometric Section View 00:01:00 Appearance, Scene and Rendering Applying Materials 00:08:00 Appearance 00:05:00 Working with Woods 00:05:00 Working with Glass 00:04:00 Scene 00:04:00 Light 00:07:00 Camera 00:04:00 Decals 00:07:00 Text 00:05:00 Options 00:04:00 Rendering Panel 00:03:00 Schedule Rendering 00:02:00 Animation Creating Motion Study 00:02:00 Animation Wizard 00:08:00 Applying Motor 00:04:00 Appearance and Camera Position 00:07:00 Walkthrough Part-1 00:09:00 Walkthrough Part-2 00:06:00 Resources Resources - Solidworks: Beginner to Advanced 00:00:00 Assignment Assignment - Solidworks: Beginner to Advanced 00:00:00

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.   Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 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 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 •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 •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 •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 •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 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •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): 00:17:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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

Highlights of the Course Course Type: Online Learning Duration: 1 to 2 hours Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about neuroscience Understand the core competencies and principles of neuroscience Explore the various areas of neuroscience Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert professional Practical Neuroscience: 30+ Exercises for a Better Brain Training Course Master the skills you need to propel your career forward in neuroscience. This course will equip you with the essential knowledge and skillset that will make you a confident professional and take your career to the next level. This comprehensive practical neuroscience course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this practical neuroscience course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This Practical Neuroscience: 30+ Exercises for a Better Brain Training at QLS Level 5 course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. This comprehensive course will teach you the theory of effective neuroscience practice and equip you with the essential skills, confidence and competence to assist you in the neuroscience industry. You'll gain a solid understanding of the core competencies required to drive a successful career in neuroscience. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for professional or for people who are aspiring to specialise in neuroscience. This Practical Neuroscience: 30+ Exercises for a Better Brain Training at QLS Level 5 course has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course is not regulated by Ofqual and is not an accredited qualification. Enrol in this practical neuroscience course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive practical neuroscience course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this neuroscience can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This practical neuroscience course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This practical neuroscience course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This practical neuroscience course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Create a Growth Mindset Welcome! Introduction 00:03:00 5 Seconds in, 5 Seconds Out 00:04:00 Ina 1, Ina 2 - Working With Inner Critic 00:05:00 3 Step Breathing Space - Genious Practice in 3 Minutes 00:04:00 Like Morning, Like Day 00:05:00 Listening Day 00:02:00 A Different Kind of Q&A 00:03:00 Explore The Palace of Your Mind 00:02:00 Slow is Sometimes Great 00:01:00 Going Back to Letters 00:04:00 Integrated Brain Day: Socializing as an Exercise for The Brain 00:03:00 Working Out The Working Memory What is Working Memory? Backwards is The New Black 00:04:00 Simplifice 00:03:00 Juggling 00:04:00 No More Multitasking, Please 00:03:00 Experiments on Reading 00:03:00 Cooking Maps 00:02:00 How to Impress (Yourself) With Mental Calculation 00:07:00 One, and Only One 00:02:00 Kim's Game 00:02:00 Downloading Information 00:03:00 Backwards Revisited 00:03:00 Best Warm up to Start The Day 00:03:00 Test Your Speed With Stroop Test 00:02:00 Integrated Brain Day: Breaking Habits on a Daily Basis 00:03:00 Grow Your Creativity Growing a Creative Mind. Alternatives 00:03:00 Random is The Most Creative 00:06:00 Fun With Rhyme 00:02:00 A Different Kind of Brainstorming 00:03:00 Best Morning Hygene for The Mind 00:04:00 Integrated Brain Day: Synestesia 00:02:00 Train Your Memory Do We Still Need to Improve Our Memory 00:01:00 Stories to Remember 00:05:00 Mnemonics 00:03:00 Same Road, New Discoveries 00:03:00 Remember Names and Faces 00:05:00 Take More Pictures With Your Mind 00:01:00 Use Visualisation to Build Positive Memories 00:05:00 Integrated Brain: A Very Precious Sip of Tea 00:03:00 Smart Habits for a Healthy brain Time to Get Primitive 00:03:00 Nap Time 00:02:00 Integrated Brain: Kindness With Nothing in Return 00:02:00 Build Your Own Personalized Practice Out of This 00:03:00 Thank You 00:01:00 Final Assessment Assessment - Practical Neuroscience: 30+ Exercises for a Better Brain 00:10:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

This course teaches you data analysis and visualisation using the versatile R language. From understanding data structures to performing advanced statistical analysis, this course equips you with the skills to extract meaningful insights from complex datasets. This Course At A Glance Accredited by CPD UK Endorsed by Quality Licence Scheme Get a deep understanding of data science, the process and the toolbox Learn about R and Rstudio Get an introduction to the basic data types in R Learn to perform arithmetic calculations on vectors Understand what is a matrix and how to analyse it Know what is factors and how to summarise it Recognise how to create a data frame Get an understanding of the relational and logical operators Learn what is a conditional statement and how to implement the same Learn about loops, functions and R packages Understand data manipulation with dplyr Data Science Course with R Programming Course Overview This comprehensive data science with R programming course is specially designed for those who are willing to get a better understanding of R programming and data science to gain proficiency in the same. This online course will help you strengthen your knowledge of data science, R and Rstudio, basics, vectors and much more. This online data science with R programming course will also help you acquire knowledge about the Matrices, factors, data frame, list, logical and relational operations and conditional statements. You will also gain an understanding of the advanced features like loops, functions R packages, regular expressions, etc., to master R language and data science. By the end of the course, you will be able to write R programmes efficiently and be able to analyse data. You will also develop the skills to become a successful data scientist or data analyst after completing this course. Who should take this course? This comprehensive data science with R programming course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of R programming. Entry Requirements There are no academic entry requirements for this data science with r programming course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This data science with r programming course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner can grasp from each section. In the assessment pass mark is 60%. Course Curriculum Data Science Overview Introduction to Data Science Data Science Career of the Future What is Data Science Data Science As a Process Data Science Toolbox Data Science Process Explained What's Next R and RStudio Engine and Coding Environment Installing R and RStudio RStudio a Quick Tour Introduction to Basics Arithmetic With R Variable Assignment Basic Data Types in R Vectors Creating a Vector Naming a Vector Arithmetic Calculations on Vectors Vector Selection Selection by Comparison Matrices What's a Matrix Analyzing Matrices Naming a Matrix Adding Columns and Rows to a Matrix Selection of Matrix Elements Arithmetic with Matrices Factors What's a Factor Categorical Variables and Factor Levels Summarizing a Factor Ordered Factors Data Frames What's a Data Frame Creating a Data Frame Selection of Data Frame Elements Conditional Selection Sorting a Data Frame Lists Why Would You Need Lists Creating a List Selecting Elements From a List Adding More Data to The List Relational Operators Equality Greater and Less Than Compare Vectors Compare Matrices Logical Operators AND, OR, NOT Operators Logical Operators with Vectors and Matrices Reverse The Result Relational and Logical Operators Together Conditional Statements The IF Statement IF…ELSE The ELSEIF Statement Loops Write a While Loop Looping with More Conditions Break Stop The While Loop What's a For Loop. Loop Over a Vector Loop Over a List Loop Over a Matrix For Loop with Conditionals Using Next and Break with For Loop Functions What Is a Function. Arguments Matching Required and Optional Arguments Nested Functions Writing Own Functions Functions with No Arguments Defining Default Arguments in Functions Function Scoping Control Flow in Functions R Packages Installing R Packages Loading R Packages Different Ways to Load a Package The Apply Family - Lapply What Is Lapply and When Is Used. Use Lapply with User-Defined Functions Lapply and Anonymous Functions Use Lapply with Additional Arguments The Apply Family - Sapply & Vapply What Is Sapply. How to Use Sapply. Sapply with Your Own Function Sapply with a Function Returning a Vector When Can't Sapply Simplify. What Is Vapply and Why Is It Used. Useful Functions Mathematical Functions Data Utilities Regular Expressions Grepl & Grep Metacharacters Sub & Gsub More Metacharacters Dates And Times Today and Now Create and Format Dates Create and Format Times Calculations with Dates Calculations with Times Getting and Cleaning Data Get and Set Current Directory Get Data From The Web Loading Flat Files Loading Excel Files Plotting Data in R Base Plotting System Base Plots Histograms Base Plots Scatterplots Base Plots Regression Line Base Plots Boxplot Data Manipulation With dplyr Introduction to dplyr Package Using The Pipe Operator (%>%) Columns Component Select() Columns Component Rename() and Rename_with() Columns Component Mutate() Columns Component Relocate() Rows Component Filter() Rows Component Slice() Rows Component Arrange() Rows Component Rowwise() Grouping of Rows Summarise() Grouping of Rows Across() Covid-19 Analysis Task Assessment Assessment - Data Science Course with R Programming Recognised Accreditation CPD Certification Service This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field. Quality Licence Scheme Endorsed The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees.     Certificate of Achievement Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. 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Course Curriculum Section 01: Introduction About the course structure 00:05:00 Why working is important? 00:04:00 The free and perfect tools 00:07:00 Our editor: Atom 00:04:00 Version control: Github 00:07:00 Python download (Mac) 00:05:00 Python download (Windows) 00:02:00 Section 02: Python Basics for Trading Introduction 00:03:00 Python Libraries 00:05:00 Iterators: for 00:08:00 Iterators: while 00:08:00 Conditionals: if & else 00:10:00 Logic gates: and & or 00:09:00 Error handling: try & except 00:09:00 Functions and calls to libraries 00:13:00 Objects and classes (1) 00:10:00 Objects and classes (2) 00:07:00 Debugging the code 00:12:00 Closing and wrap up 00:01:00 Section 03: Trading Basics Introduction 00:03:00 Fundamental vs Technical Analysis 00:04:00 Stocks vs CFDs 00:05:00 Long and Short positions 00:04:00 Takeprofit and Stoploss 00:03:00 Setting a real Stoploss 00:08:00 Limit and Market orders 00:10:00 Don't forget the spread 00:04:00 Stock data visualisation: candles 00:08:00 Technical Indicators: about 00:05:00 Exponential Moving Average 00:08:00 EMA use and interpretation 00:06:00 Relative Strength Index 00:07:00 Stochastic Oscillator 00:09:00 Closing and wrap up 00:01:00 Section 04: Bot Code General Structure Introduction 00:02:00 Overview 00:08:00 The Entry Strategy 00:10:00 About Tradingview 00:12:00 When to enter (1) 00:08:00 When to enter (2) 00:08:00 Open and hold a position 00:12:00 Closing a position 00:08:00 Review (1) 00:06:00 Review (2) 00:13:00 Closing 00:02:00 Section 05: Github Basics Introduction 00:04:00 Download and install Github 00:01:00 Create a repo 00:10:00 Working with branches 00:13:00 Section 06: Building Your Bot Introduction 00:05:00 Create the first bot file 00:07:00 Building the bot scheme 00:08:00 Complete your code scheme (1) 00:11:00 Complete your code scheme (2) 00:11:00 Complete your code scheme (3) 00:18:00 A logger to remember (1) 00:14:00 A logger to remember (2) 00:14:00 Organising your code 00:07:00 Main function: run bot 00:23:00 Link the bot and the library 00:08:00 Traderlib control functions (1) 00:12:00 Traderlib control functions (2) 00:13:00 Check if tradable function 00:06:00 Set stoploss function 00:10:00 Set takeprofit function 00:04:00 Load historical data function 00:01:00 Get open positions function 00:04:00 Submit and cancel order functions 00:04:00 Check positions function 00:09:00 The Tulipy libraries 00:07:00 Importing all the libraries 00:03:00 First filter: get general trend 00:19:00 Second filter: get instant trend 00:14:00 Third filter: RSI 00:08:00 Fourth filter: Stochastic Oscillator 00:14:00 Enter position (1) 00:13:00 Enter position (2) 00:11:00 Enter position (3) 00:15:00 Enter position (4) 00:08:00 Last check before opening 00:13:00 Exit position and get out 00:10:00 Linking everything (1) 00:12:00 Linking everything (2) 00:12:00 Linking everything (3) 00:15:00 Fixing a mistake: going Short 00:05:00 Handling all your variables 00:18:00 Closing and wrap up 00:01:00 Run function scheme clarification and rebuild 00:13:00 Section 07: Integrating the Broker API Introduction 00:03:00 The Alpaca Python API Wrapper 00:07:00 Initialising the REST API 00:09:00 Running the program (crash!) 00:06:00 Integration with check account (1) 00:08:00 Integration with check account (2) 00:05:00 Clean open orders function 00:10:00 Importing the trading library 00:04:00 Running the main 00:05:00 Check position function 00:09:00 Check if asset exists function 00:08:00 Fetching barset data (theory) 00:07:00 Fetching barset data (practice) 00:12:00 Updating the code for the Alpaca API V2 (explanation) 00:03:00 Updating the code for the Alpaca API V2 (implementation) 00:08:00 Organizing data with Pandas 00:06:00 Get general trend function (1) 00:08:00 Reframing the timeframe with Pandas 00:23:00 Get general trend function (2) 00:13:00 Get instant trend function 00:08:00 Get RSI function 00:06:00 Get Stochastic function 00:10:00 Get current price function 00:05:00 Finishing get shares amount 00:09:00 Opening a position (1) 00:12:00 Opening a position (2) 00:09:00 Check the open position 00:07:00 Cancelling the order (1) 00:20:00 Cancelling the order (2) 00:08:00 Making sure we cancelled 00:03:00 Get average entry price function 00:10:00 Fixing bugs when getting price 00:18:00 Check Stochastic crossing 00:02:00 Holding an open position 00:11:00 Submitting the exit order 00:08:00 Closing position and out (1) 00:08:00 Closing position and out (2) 00:10:00 Closing and wrap up 00:01:00 Section 08: Running the Trading Bot Introduction 00:03:00 Filtering asset by price and volume 00:07:00 Get the bot ready to trade 00:04:00 Running the Trading Bot with AAPL 00:09:00 A real open position 00:08:00 Debugging and bug fixing 00:12:00 Fixing one (last) bug 00:02:00 Running the bot with TSLA 00:10:00 Discussing EMA implementations 00:12:00 Closing and wrap up 00:02:00

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