32684 Development courses

Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

Are you someone who wants to become an ideal lawyer to secure intellectual and financial properties of your clients? Or are you someone who is finding one? If yes, then this course in finding the perfect lawyer will be able to help you in your journey toward secured intellectual and financial property ownership or assist you in becoming the ideal lawyer anyone would want! Description: What are the characteristics you need to find a lawyer for you to feel safe and secure? In this course, you will be able to learn why you or your business needs to have their lawyer. This course is designed to make you realise what type of lawyer you need. You will also know the different kinds of lawyers in this course and be taught about each type. Lastly, you will be trained to search the ideal lawyer or how lawyers can promote themselves for the potential clients to check. Who is the course for? Businessmen and other professionals who are in need of lawyers to protect their financial and intellectual properties. Lawyers who want to become the ideal lawyer clients would prefer. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: Finding the Perfect Lawyer is a useful qualification to possess, and would be beneficial for the following careers: Businessmen Entrepreneurs Financial Advisers Lawyers Legal Advisers Top Executives. Finding the Perfect Lawyer Introduction 00:15:00 Why A Perfect Lawyer? 01:00:00 Types Of A Perfect Lawyer 01:00:00 How to Find For an Attorney 01:00:00 Why You Need for an Attorney 01:00:00 Interviewing For A Potential Attorneys 01:00:00 Build A Good Business Relationship 01:00:00 How Will I Know When It's Time to See a Specialist 00:30:00 Doing Your Own Footwork 01:00:00 Saving Money on an Attorney 01:00:00 Essential Information Resources 01:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description: Hold the attention and suspense of the reader with Thriller Writing Thriller can be both enjoyable yet challenging tasks. A thriller writer needs to know a lot of things including the knowledge of science, reader's interest, the understanding of writing patterns, and more. The Creative Writing Course - Thriller course is prepared to fulfil the thirst of the thriller writer. The course teaches you the writing pattern or formats of a thriller and helps you to create a story and protagonist that will hold the suspense of the readers. You will learn how to write a thriller easily, then submit it to the publisher, and finally the procedures of publication. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Creative Writing Course - Thriller is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Creative Writing Course - Thriller is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Writing The Thriller Introduction to Writing the Thriller 00:30:00 The Thriller: Form and Function 00:30:00 Writing the Thriller: Lesson One 00:30:00 Writing the Thriller: Lesson Two 00:30:00 Exercise 1 - Building Your Thriller 00:30:00 Writing the Thriller: Lesson Three 00:30:00 Exercise 2 - Building Your Thriller 00:30:00 Writing the Thriller: Lesson Four 00:30:00 Exercise 3 - Building Your Thriller 00:30:00 Writing the Thriller: Lesson Five 00:30:00 Exercise 4 - Building Your Thriller 00:30:00 Writing the Thriller: Lesson Six 00:30:00 Mock Exam Mock Exam - Creative Writing Course - Thriller 00:20:00 Final Exam Final Exam - Creative Writing Course - Thriller 00:20:00 Order Your Certificates and Transcripts Order Your Certificates and Transcripts 00:00:00

In this competitive job market, you need to have some specific skills and knowledge to start your career and establish your position. This Investment Banking: Venture Capital Fundraising for Startups will help you understand the current demands, trends and skills in the sector. The course will provide you with the essential skills you need to boost your career growth in no time. The Investment Banking: Venture Capital Fundraising for Startups will give you clear insight and understanding about your roles and responsibilities, job perspective and future opportunities in this field. You will be familiarised with various actionable techniques, career mindset, regulations and how to work efficiently. This course is designed to provide an introduction to Investment Banking: Venture Capital Fundraising for Startups and offers an excellent way to gain the vital skills and confidence to work toward a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited Investment Banking: Venture Capital Fundraising for Startups is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this Investment Banking: Venture Capital Fundraising for Startups. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. 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 £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The Investment Banking: Venture Capital Fundraising for Startups will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum Section 01: Welcome to the Course! Welcome to this Course on Capital Raising for Entrepreneurs 00:05:00 Section 02: Let's Get Started Right Away What types of investors are out there? 00:12:00 What is the difference between Venture Capital and Private Equity? 00:14:00 What stage is your business at? 00:14:00 How Much Money Should You Raise? 00:04:00 What is the Difference between a Pre Money and Post Money Valuation 00:01:00 Section 03: An introduction to Startups Startup Essentials - Markets 00:05:00 Startup Essentials - Profits 00:06:00 Startup Essentials - Business Plan 00:05:00 Startup Essentials - Capital 00:05:00 Startup Essentials - Value 00:06:00 Startup Essentials - Investors 00:05:00 Section Text Summary PDF for Download 00:16:00 Section 04: Do You Really Understand Venture Capitalists? Do You Really Understand Venture Capitalists? 00:14:00 Do You Match Their Criteria? 00:18:00 Four Key Questions to Ask? 00:03:00 Understanding the Investment Process 00:18:00 Section 05: How to Understand If You Are Talking to the Right Investor Introduction: Understanding Your VCs; A Case Study 00:02:00 What Type Of Investor Are You Talking To? 00:12:00 A Detailed Breakdown of Different Types of Private Equity Funds 00:05:00 What is their Ideal Investment Size? 00:06:00 What Stage Do They Invest At? 00:03:00 Stage of Business Financing from a VC Perspective 00:05:00 How Can You Define Venture Capitalists' Sector Interest? 00:03:00 What Part Does Geography Play? 00:06:00 What is meant by Style and Structure? 00:05:00 What is meant by Key Investment Criteria? 00:03:00 Section Summary: Do You Understand VCs? 00:14:00 Section 06: Looking at Things from the VC Point of View What Factors are important to VCs? 00:10:00 Considering Valuation from the VC Perspective 00:06:00 How do Investors value a Startup? 00:12:00 How do Investors Value a Series an Investment? 00:07:00 How do VCs look at your Market? 00:07:00 What do VCs think about your Product or Service? 00:09:00 How Do VCs Evaluate You and your Management Team? 00:10:00 Why is Exit Strategy important to VCs? 00:07:00 Why are Barriers to Entry important? 00:07:00 How do VCs consider your Competition? 00:04:00 What Financial Information is important to VCs? 00:03:00 What is the typical VC Decision Making Process? 00:09:00 Seed Stage VC's Decision Tree 00:05:00 Project: Evaluate Your Own Startup 00:02:00 Section 07: What Questions Should You Ask Venture Capital? 36 Questions to Ask a VC Overview 00:02:00 36 Questions to Ask a VC Part 1 - Fund Profile 00:03:00 36 Questions to Ask a VC Part 2 - Investment Style 00:02:00 36 Questions to Ask a VC Part 3 - Deal Flow 00:03:00 36 Questions to Ask a VC Part 4 - Process 00:03:00 36 Questions to Ask a VC Part 5 - Structure 00:03:00 36 Questions to Ask a VC Part 6 - Value Added 00:03:00 Key Questions That You Can Expect a VC to Ask You 00:06:00 Section 08: How to Email Venture Capital and Angel Investors How to Write an Introductory Email to an Investor 00:11:00 The Power of Forwardable Emails 00:02:00 How NOT to email investors 00:04:00 How to Find an Investors Email Address (if you don't have it) 00:09:00 Section 09: What You Need to Know to Present Your Business to Investors How to Deliver a 60 Second Pitch 00:08:00 The Sixteen Magic Words Investors Want to Hear from You 00:21:00 How to Write a One Pager for a VC 00:18:00 Top Tips on Preparing to Pitch Investors 00:12:00 How to prepare a Pitch Deck for an Investor 00:19:00 How to Prepare a Business Plan and Executive Summary 00:02:00 How to Prepare a Financing Strategy 00:02:00 Key Elements of the Financial Plan 00:11:00 Section 10: Startup Fundraising and Pitching Startup Fundraising - Getting Started 00:09:00 19 Reasons VCs May Say No 00:09:00 Communicating Your Vision 00:03:00 The Business Plan; Overview and Communication 00:07:00 Business Plan Core Contents 00:08:00 The Financial Plan 00:16:00 The Pitching Process and Investor Returns 00:08:00 Post Mortems 00:07:00 What are Investors looking for? 00:07:00 Section 11: How to Deliver Winning Presentation to Investors What do Investors Want? 00:13:00 Outline Presentation Checklist 00:19:00 What is TAM, SAM and SOM and why are they important? 00:15:00 AIDA - Why Pitching VCs Is Like Buying a Car! 00:11:00 Selling Your Pitch 00:13:00 Pitching to Win! 00:13:00 How to Run the Meeting 00:14:00 Outline Management Presentation 00:15:00 Defending Your Plan 00:17:00 ACTIVITY: Create Your Own Presentation 00:01:00 Section 12: Managing the Fundraising Process How do Venture Capitalists Source Deals? 00:06:00 How to find Angel Investors 00:08:00 How to Find Venture Capital Investors 00:02:00 BONUS: How to Find a Venture Capital Investor for Your Tech Company 00:09:00 What Happens Next? The Investment Process 00:08:00 How to Manage the Investment Process 00:08:00 Section 13: Venture Capital Term Sheets What is a Term Sheet Part 1 00:08:00 What is a Term Sheet Part 2 00:11:00 Key Concepts in Term Sheets 00:10:00 What is a Term Sheet Trying to Achieve? 00:10:00 26 Key Components in VC Term Sheets 1 -5 00:08:00 26 Key Components in VC Term Sheets 6 - 10 00:08:00 26 Key Components in VC Term Sheets 11 - 15 00:08:00 26 Key Components in VC Term Sheets 16 - 20 00:30:00 26 Key Components in VC Term Sheets 21 - 26 00:09:00 Negotiating Term Sheets: Entrepreneurs Perspective 00:09:00 Negotiating Term Sheets: VC Perspective 00:11:00 Negotiating Term Sheets: Mutual Issues of Concern 00:02:00 US Style VC Term Sheet Example 00:12:00 Section 14: Equity Crowdfunding for Entrepreneurs What is Crowdfunding? 00:03:00 The Advantages of Equity Crowdfunding for the Investor 00:14:00 The Disadvantages of Crowdfunding for the Investor 00:12:00 Section 15: How to Evaluate a Crowdfunding Opportunity? Introduction to How to Evaluate a Crowdfunding Opportunity 00:01:00 The Key Data You Need To Know For Any Opportunity 00:03:00 Let's take a look now at Management Skills 00:03:00 Management Experience is important as well 00:02:00 You must take a look at the Management's Commitment! 00:03:00 Product Market 00:03:00 So, how unique is this product? 00:03:00 What is the Competition like? 00:03:00 Does the Product have (all important) traction? 00:03:00 How profitable is the product and therefore the investment? 00:03:00 Let's take a look at the most critical factor, Cash Flow! 00:03:00 Finally, let's see what this all means for your Investment Returns 00:03:00 Discover how you can turn this information into a Methodology! 00:02:00 Let's Summarise this Section with the 10 Most Important Factors 00:02:00 Section 16: Introduction with Andrew Monk, CEO iolight about his Crowdfunding Experience Introduction 00:05:00 Why did you go for Equity Crowdfunding? 00:04:00 What did you do early on to ensure success? 00:03:00 How did you go about lining up your 25% 00:02:00 Did you set about trying to collect email addresses? 00:03:00 Let's have the Investor Conversation 00:06:00 Are there any mistakes looking back you may have made? 00:08:00 So what is it like by the end of week three? 00:07:00 How does Crowdcube get the money to you? 00:09:00 Are there any other tools you used that you can recommend? 00:04:00 Bonus: Discussion about Campaign Videos 00:04:00 Bonus: Detailed Notes on this Section to Download - PDF Attached 00:16:00 Section 17: Summary and Wrap Up Course Summary and Wrap Up 00:03:00 Section 18: Additional File Additional File 00:00:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics 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 Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics 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: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

Delving into the essentials of business analysis, this CPD-accredited course offers learners a structured pathway to understand how organisations operate, make decisions, and adapt to change. It introduces time-tested concepts in stakeholder engagement, requirements gathering, process modelling, and effective communication within business environments. Whether you're new to the subject or looking to build upon existing knowledge, the course provides clarity on the core principles that shape strategic and operational decision-making. Designed for flexibility, the course is accessible entirely online—no seminar rooms or boardrooms in sight. Each module is arranged with clarity and intention, helping learners navigate key topics with ease. With a focus on relevance and usability, this training supports those aiming to understand the analytical side of business without wading through overhyped jargon. Learn at your pace, from anywhere, and take your understanding of business processes to a more confident level. Course Curriculum: Module 01: An Introduction to Business Analysis Module 02: The Necessity of a Business Analyst Module 03: Addressing Requirements Module 04: Needs Assessment Module 05: Business Analysis Planning Module 06: Strategy Analysis Module 07: Stakeholder Analysis Module 08: Requirements Elicitation Module 09: Requirements Analysis Module 10: Traceability and Monitoring Module 11: Solution Evaluation Course Assessment You will immediately be given access to a specifically crafted MCQ test upon completing an online module. For each test, the pass mark will be set to 60%. CPD 10 CPD hours / points Accredited by The CPD Certification Service Who is this course for? The Business Analysis - CPD Accredited training is ideal for highly motivated individuals or teams who want to enhance their skills and efficiently skilled employees. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Learn the essential skills and knowledge you need to excel in your professional life with the help & guidance from our Business Analysis - CPD Accredited training.

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Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Recruitment and Virtual Interview Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Recruitment and Virtual Interview Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Recruitment and Virtual Interview Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Recruitment and Virtual Interview Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Recruitment and Virtual Interview? 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 Recruitment and Virtual Interview 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 Recruitment and Virtual Interview 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 Recruitment and Virtual Interview does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Recruitment and Virtual Interview 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 Recruitment and Virtual Interview is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Module 01: The Recruitment Industry The Recruitment Industry 00:27:00 Module 02: The Recruitment Process The Recruitment Process 00:47:00 Module 03: In-House Recruitment In-House Recruitment 00:22:00 Module 04: The UK Recruitment Legislation The UK Recruitment Legislation 00:29:00 Module 05: An Introduction to Virtual Interviewing An Introduction to Virtual Interviewing 00:16:00 Module 06: Interviewer's Perspective Interviewer's Perspective 00:15:00 Module 07: Interview Preparation Interview Preparation 00:30:00 Module 08: Picking a Tech to Use Picking a Tech to Use 00:30:00 Module 09: Attract and Hire the Best Talents Attract and Hire the Best Talents 00:15:00 Module 10: Final Thoughts and Onboarding Final Thoughts and Onboarding 00:29:00

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