44 Inference courses in Sheffield delivered Online

[vc_row][vc_column][vc_column_text] Description: This Python Basic to Advanced for Data Science Online Course is a great way to get started in programming. It covers the study of the Python language used to build most of the world's object-oriented systems. The course is for interested students with a good level of computer literacy who wish to acquire programming skills. It is also ideal for those who wish to move to a developer role or areas such as software engineering. This is a great course to develop your coding skills. This Python Basic to Advanced for Data Science Online Course is an ideal preliminary to the Object-Oriented Programming using Python. Join the course now! 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. Certification: After completing 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. 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; The UK & internationally recognized 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 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.[/vc_column_text][/vc_column][/vc_row] Python 3 Beginners Module 01 Introduction FREE 00:29:00 Starter Examples 00:33:00 Learning C Concepts 00:13:00 Module 02 Data Types and Inference 00:20:00 Sizeof and IEEE 754 00:33:00 Constants L and R Values 00:11:00 Operators and Precedence 00:25:00 Literals 00:26:00 Module 03 Classes and Structs FREE 00:22:00 Enums 00:14:00 Unions 00:16:00 Introduction to Pointers 00:11:00 Pointers and Array Indexing 00:12:00 Using Const with Pointers 00:09:00 Pointers to String Literals 00:12:00 References 00:14:00 Smart Pointers 00:22:00 Arrays 00:15:00 Standard Library Strings 00:13:00 More Standard Library Strings 00:18:00 Functions 00:06:00 More Functions 00:16:00 Function Pointers 00:15:00 Control Statements 00:18:00 Python 3 Intermediate Module 04 Installing Python FREE 00:17:00 Documentation 00:30:00 Command Line 00:17:00 Variables 00:29:00 Simple Python Syntax 00:15:00 Keywords 00:18:00 Import Module 00:17:00 Additional Topics 00:23:00 Module 05 If Elif Else 00:31:00 Iterable 00:10:00 For 00:11:00 Loops 00:20:00 Execute 00:05:00 Exceptions 00:18:00 Data Types 00:24:00 Module 06 Number Types 00:28:00 More Number Types 00:13:00 Strings 00:20:00 More Strings 00:11:00 Files 00:08:00 Lists 00:15:00 Dictionaries 00:04:00 Tuples 00:07:00 Sets 00:09:00 Module 07 Comprehensions 00:10:00 Definitions 00:02:00 Functions 00:06:00 Default Arguments 00:06:00 Doc Strings 00:06:00 Variadic Functions 00:07:00 Factorial 00:07:00 Function Objects 00:07:00 Module 08 Lambda 00:11:00 Generators 00:06:00 Closures 00:10:00 Classes 00:09:00 Object Initialization 00:05:00 Class Static Members 00:07:00 Classic Inheritance 00:10:00 Data Hiding 00:07:00 Python 3 Advanced Iterators and Generators FREE 00:16:00 Regular Expressions 00:19:00 Introspection and Lambda Functions 00:27:00 Metaclasses and Decorators 00:24:00 Modules and Packages 00:25:00 Working with APIs 00:15:00 Metaprogramming Primer 00:19:00 Decorators and Monkey Patching 00:21:00 XML and JSON Structure 00:10:00 Generating XML and JSON 00:17:00 Parsing XML and JSON 00:19:00 Implementing Algorithms 00:19:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description: This diploma in C++ and Python programming course is a great way to get started in programming. It covers the study of the C++ and Python group of languages used to build most of the world's object oriented systems. The course is for interested students with a good level of computer literacy who wish to acquire programming skills. It is also ideal for those who wish to move to a developer role or areas such as software engineering. This is a great course to develop your coding skills. It teaches key features of imperative programming using C and is an ideal preliminary to the Object-Oriented Programming using Python. Join the course now! 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 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. 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 recognized 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 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. Python 3 Beginners Module 01 Introduction FREE 00:29:00 Starter Examples 00:33:00 Learning C Concepts 00:13:00 Module 02 Data Types and Inference 00:20:00 Sizeof and IEEE 754 00:33:00 Constants L and R Values 00:11:00 Operators and Precedence 00:25:00 Literals 00:26:00 Module 03 Classes and Structs FREE 00:22:00 Enums 00:14:00 Unions 00:16:00 Introduction to Pointers 00:11:00 Pointers and Array Indexing 00:12:00 Using Const with Pointers 00:09:00 Pointers to String Literals 00:12:00 References 00:14:00 Smart Pointers 00:22:00 Arrays 00:15:00 Standard Library Strings 00:13:00 More Standard Library Strings 00:18:00 Functions 00:06:00 More Functions 00:16:00 Function Pointers 00:15:00 Control Statements 00:18:00 Python 3 Intermediate Module 04 Installing Python FREE 00:17:00 Documentation 00:30:00 Command Line 00:17:00 Variables 00:29:00 Simple Python Syntax 00:15:00 Keywords 00:18:00 Import Module 00:17:00 Additional Topics 00:23:00 Module 05 If Elif Else 00:31:00 Iterable 00:10:00 For 00:11:00 Loops 00:20:00 Execute 00:05:00 Exceptions 00:18:00 Data Types 00:24:00 Module 06 Number Types 00:28:00 More Number Types 00:13:00 Strings 00:20:00 More Strings 00:11:00 Files 00:08:00 Lists 00:15:00 Dictionaries 00:04:00 Tuples 00:07:00 Sets 00:09:00 Module 07 Comprehensions 00:10:00 Definitions 00:02:00 Functions 00:06:00 Default Arguments 00:06:00 Doc Strings 00:06:00 Variadic Functions 00:07:00 Factorial 00:07:00 Function Objects 00:07:00 Module 08 Lambda 00:11:00 Generators 00:06:00 Closures 00:10:00 Classes 00:09:00 Object Initialization 00:05:00 Class Static Members 00:07:00 Classic Inheritance 00:10:00 Data Hiding 00:07:00 Python 3 Advanced Iterators and Generators FREE 00:16:00 Regular Expressions 00:19:00 Introspection and Lambda Functions 00:27:00 Metaclasses and Decorators 00:24:00 Modules and Packages 00:25:00 Working with APIs 00:15:00 Metaprogramming Primer 00:19:00 Decorators and Monkey Patching 00:21:00 XML and JSON Structure 00:10:00 Generating XML and JSON 00:17:00 Parsing XML and JSON 00:19:00 Implementing Algorithms 00:19:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

This video course will help you learn all the basic and advanced concepts of Microsoft Excel 2019. You'll start with Excel basics and slowly move to the advanced concepts in Excel. Each section is accompanied by an exercise at the end to practice what you have learned.

Duration 5 Days 30 CPD hours This course is intended for In order to be successful in this course you should have incoming hands-on experience with another programming language. This course is not for non-developers or new developers. Possible roles that may attend this course include: Software Developers: Professionals who have been working with other programming languages and want to expand their skillset by learning Java and its object-oriented features. Web Developers: Those who work on web applications and want to enhance their back-end development capabilities with Java. Mobile App Developers: Developers who wish to enter the world of Android app development, where Java is a widely used language for creating mobile applications. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how?it relates to OO programming and the Object Model Learn to use Java exception handling Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Become familiar with the concept of functional programming using Lambda Expressions Process large amounts of data using the Stream API introduced in Java 8 Discover the new Date/Time API Use the JDBC API for database access Work with annotations Take advantage of the Java tooling that is available with the programming environment being used in the class Java 8 Features: Lambda Expressions, Method and Constructor references, The Streams API, Collectors, The Optional class Geared for experienced developers, Basic Java Programming for Developers New to OO, this hands-on, workshop-style course will provide you with an immersive learning experience that will expand your skillset and open doors to new opportunities within the ever-growing technology landscape. Mastering Java and its powerful capabilities will provide you with the competitive edge you need to stand out in today's fast-paced development world. Working in a hands-on learning environment led by our expert coach, you?ll thoroughly explore the foundations of the Java platform, essential programming concepts, and advanced topics, ensuring you acquire a strong understanding of the language and its ecosystem. The object-oriented programming principles taught in this course promote code reusability and maintainability, enabling you to streamline development processes and reduce long-term costs. As you progress through the course, you will also gain familiarity with using an IDE, enhancing your development workflow and collaboration with other Java developers, enabling you to integrate seamlessly into new projects and teams. You?ll also gain practical experience in applying the concepts and techniques learned, solidifying your newly acquired skills and facilitating their direct application in real-world scenarios. You?ll exit this course empowered to create robust, scalable, and efficient Java-based applications that drive innovation and growth for your organization The Java Platform The Java Platform Lifecycle of a Java Program Responsibilities of JVM Documentation and Code Reuse Using the JDK Explain the JDK?s file structure Use the command line compiler to compile a Java class Use the command line Java interpreter to run a Java application class The IntelliJ Paradigm Introduce the IntelliJ IDE The Basics of the IntelliJ interface IntelliJ Projects and Modules Creating and running Java applications Writing a Simple Class Write a Java class that does not explicitly extend another class Define instance variables for a Java class Create object instances Primitives vs Object References Implement a main method to create an instance of the defined class Adding Methods to the Class Write a class with accessor methods to read and write instance variables Write a constructor to initialize an instance with data Write a constructor that calls other constructors of the class to benefit from code reuse Use the this keyword to distinguish local variables from instance variables Object-Oriented Programming Real-World Objects Classes and Objects Object Behavior Methods and Messages Inheritance, Abstraction, and Polymorphism Encapsulation Inheritance Method Overriding Polymorphism Essential Java Programming Essential Java Programming Language Statements Arithmetic operators Operators to increment and decrement numbers Comparison operators Logical operators Return type of comparison and logical operators Use for loops Switch Expressions Switch Expressions and yield Using Strings and Text Blocks Create an instance of the String class Test if two strings are equal Get the length of a string Parse a string for its token components Perform a case-insensitive equality test Build up a string using StringBuffer Contrast String, StringBuffer,and StringBuilder Compact Strings Text Blocks Specializing in a Subclass Constructing a class that extends another class Implementing equals and toString Writing constructors that pass initialization data to parent constructor Using instanceof to verify type of an object reference Pattern matching for instanceof Overriding subclass methods Safely casting references to a more refined type Fields and Variables Discuss Block Scoping Rules Distinguish between instance variables and method variables within a method Explain the difference between the terms field and variable List the default values for instance variables Final and Static fields and methods Local Variable type inference Using Arrays Declaring an array reference Allocating an array Initializing the entries in an array Writing methods with a variable number of arguments Records Data Objects in Java Introduce records as carrier of immutable data Defining records Java Packages and Visibility Use the package keyword to define a class within a specific package Discuss levels of accessibility/visibility Using the import keyword to declare references to classes in a specific package Using the standard type naming conventions Visibility in the Java Modular System Correctly executing a Java application class The Java modular system Defining Modules Inheritance and Polymorphism Write a subclass with a method that overrides a method in the superclass Group objects by their common supertype Utilize polymorphism Cast a supertype reference to a valid subtype reference Use the final keyword on methods and classes to prevent overriding Interfaces and Abstract Classes Define supertype contracts using abstract classes Implement concrete classes based on abstract classes Define supertype contracts using interfaces Implement concrete classes based on interfaces Explain advantage of interfaces over abstract classes Explain advantage of abstract classes over interfaces Static, default and private methods in interfaces Sealed classes Introduce Sealed classes The sealed and permits modifiers Sealed Interfaces Exception Handling Introduction to Exception Handling Introduce the Exception architecture Defining a try/catch blocks Checked vs Unchecked exceptions Exceptions Defining your own application exceptions Automatic closure of resources Suppressed exceptions Handling multiple exceptions in one catch Helpful Nullpointers Enhanced try-with-resources Java Developer's Toolbox Developing applications Introduce the wrapper classes Explain Autoboxing and Unboxing Converting String representations of primitive numbers into their primitive types Defining Enumerations Using static imports Deprecating methods Advanced Java Programming Introduction to Generics Generics and Subtyping Bounded Wildcards Generic Methods Legacy Calls To Generics When Generics Should Be Used Lambda Expressions and Functional Interface Understanding the concept of functional programming Writing lambda expressions Understanding functional interfaces Collections Provide an overview of the Collection API Review the different collection implementations (Set, List and Queue) Explore how generics are used with collections Examine iterators for working with collections Using Collections Collection Sorting Comparators Using the Right Collection Lambda expressions in Collections Bonus Topics: Time Permitting Streams Understanding the problem with collections in Java Thinking of program solutions in a declarative way Use the Stream API to process collections of data Understand the difference between intermediate and terminal stream operations Filtering elements from a Stream Finding element(s) within a Stream Collecting the elements from a Stream into a List takeWhile and dropWhile intermediate operations Collectors Using different ways to collect the items from a Stream Grouping elements within a stream Gathering statistics about numeric property of elements in a stream

In this course, we look at a number of advanced Excel techniques all aimed at helping you make sense of the numbers in your business. Each section in the course contains an exercise for practice and quiz. The course is created using Excel 2019/365 for Windows.

This course aims to teach the programming language C++ with an emphasis on the modern features introduced in C++17. The course will cover both old and new concepts in C++, including classes, operator overloading, inheritance, polymorphism, templates, and concurrency. By the end of the course, the students will have gained the knowledge needed to become proficient C++ developers.

Learn Java programming step-by-step with 250 core features and 200+ code examples, perfect for absolute beginners. This hands-on course covers everything from basic concepts to advanced topics such as functional programming and exception handling using JShell and Eclipse as an IDE. Gain a solid foundation in Java and kickstart your programming career.

Who is this course for? SketchUp Night Training Courses. This course is designed for professionals and students interested in enhancing their SketchUp skills through evening sessions. Whether you're a beginner looking to learn the basics or an experienced user seeking advanced techniques, this course offers tailored instruction to suit various skill levels during evening hours. Click here for more info: Website 1-on-1 sessions. Mon to Sat between 9 am and 7 pm  Course Duration: 10 hours Method: 1-on-1 (In-person or Live Online) Design Your Own Template Craft custom templates 2D Geometry Essentials Construct fundamental 2D shapes (lines, arcs, circles, rectangles) Grasp the concept of geometric stickiness Exploring 3D Geometry Develop basic 3D shapes Master 3D geometric stickiness Visualize your model in 3D Effective Model Organization Organize your model effectively using layers Geometry Shaping Tools Shape geometry with the Push/Pull tool Manipulate geometry by moving entities Maintain coplanar geometry integrity Connect and generate complex forms Lock inferences for precision Expedite form generation Restore and refine surfaces Create and apply surfaces to your model Employ mirroring and array techniques Enhancing Visuals Apply materials for enhanced visuals Craft 3D text elements Utilize essential tools for creating and manipulating 3D structures Integration and Expansion Integrate component models from the 3D Warehouse Explore display options and styles Position and export models to Google Earth Model Efficiency Techniques Overcome stickiness challenges in your model Optimize modeling efficiency with component nesting Understand the impact of scaling on similar components Leverage groups and components for isolating geometry Efficiently manage components using the Component Browser 3D Warehouse Collaboration Access and share components via the 3D Warehouse Harness the power of dynamic components Master component inferencing and editing Combine and integrate components seamlessly Integration and Multimedia Import external sites into SketchUp Incorporate photographs into your projects Employ the Follow Me tool effectively Enhance your designs with the Materials Browser Collaborate with the 3D Warehouse community Fine-tune your model's style Interactive Presentations Create immersive scene-based walk-throughs Generate sections and animated scenes for compelling presentations Export and Integration Seamlessly export your work to AutoCAD and LayOut Learning Outcomes for Designers after this course: SketchUp Proficiency: Acquire mastery of essential 3D modeling and design tools. Advanced Modeling Skills: Apply intricate modeling techniques for architectural and interior components. Effective Space Planning: Organize interior spaces efficiently with space planning expertise. Architectural Precision: Create detailed architectural models and facades with precision. Custom Furniture Design: Craft bespoke furniture designs that enhance interior spaces. Texture Realism: Apply textures skillfully to achieve lifelike visualizations. Compelling Visual Presentations: Present design concepts with captivating visualizations. Effective Presentation Skills: Showcase ideas convincingly to clients and stakeholders. Professional Collaboration: Communicate seamlessly with industry professionals using SketchUp. Workflow Streamlining: Enhance project efficiency by streamlining design workflows for rapid iterations. Additional Benefits: Complimentary Portfolio Review Mock Interviews for Skill Enhancement Skills Acquired: Proficient SketchUp Mastery: Gain expertise in using SketchUp for 3D modeling, design, and visualization. Advanced Rendering Techniques: Learn to create realistic renders using plugins like V-Ray or Twilight Render. Efficient Workflow: Develop skills to streamline your design process and enhance productivity. Collaboration and Presentation: Explore techniques for collaborative work and compelling project presentations. Job Opportunities: Architectural Designer: Create detailed 3D models and visualizations for architectural projects. Interior Designer: Design and visualize interior spaces for residential and commercial clients. Landscape Architect: Develop 3D landscape designs and presentations for outdoor spaces. Freelance 3D Artist: Offer your services for various projects, from architectural visualization to product modeling. Visualization Specialist: Provide visualization services to real estate agencies, design firms, or marketing companies. Why Us? Personalized Training: Dive into SketchUp with exclusive coaching from experienced architects and designers. Enjoy 1-on-1, in-person sessions at (SW96DE) or participate in live online classes. Flexible Schedule: We're available Monday to Saturday from 9 am to 7 pm, ensuring learning fits into your busy life. Tailored Tutorials: Take home custom video tutorials crafted to enhance your SketchUp skills. Comprehensive Learning: Access a digital reference book for thorough revision, ensuring a deep understanding of every SketchUp concept. Continuous Support: Enjoy ongoing assistance via phone or email, even after the course ends, ensuring your continued success. Adaptable Syllabus: We customize the syllabus and projects to meet your specific needs, ensuring focused learning on what matters most to you. Official Certification: Certificate upon course completion, validating your SketchUp expertise. Why Choose Us? Individualized Support: Our courses, ranging from 10 to 120 hours, provide unwavering assistance at every stage. Personalized homework assignments and post-course support pave the way for mastering SketchUp with expert guidance. Personal Attention, No Crowded Classes: Experience the intimacy of one-on-one learning. Say goodbye to overcrowded classrooms, ensuring you receive the focused attention you deserve in a confident and comfortable environment. Financial Flexibility: Your educational journey shouldn't strain your finances. We offer a range of payment plans tailored to your needs. Explore the available options and embark on your SketchUp learning adventure today. Expert Instructors, Real-world Expertise: Our instructors, meticulously chosen for their industry expertise and passion for teaching, are dedicated to imparting invaluable SketchUp skills to eager learners.

A comprehensive, simple, visual guide and a super-easy course using SAS with no installation on your computer necessary. This course uses the latest SAS Studio offered through SAS OnDemand and it's completely free. 12+ hours of knowledge-packed lectures, videos, quiz questions, followed by two practical and hands-on guided exercises and projects.

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: Apply descriptive statistics, distributions, and probability theory to summarise and visualise data Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data Use Python and R to implement statistical and machine learning methods Interpret and communicate the results of your analysis using appropriate metrics and visualisations Solve real-world problems and scenarios using statistics and probability Why choose this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 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 Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course for? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge Students and researchers who want to learn the mathematical foundations of data science and machine learning Professionals and managers who want to understand and apply data-driven decision making Hobbyists and enthusiasts who want to explore and learn from data Anyone who loves statistics and probability and wants to challenge themselves Career path Data Scientist (£35,000 - £55,000) Machine Learning Engineer (£40,000 - £60,000) Statistician (£35,000 - £55,000) Data Analyst (£40,000 - £60,000) Business Intelligence Analyst (£45,000 - £65,000) Senior Data Analyst (£50,000 - £70,000) Prerequisites This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 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 £135 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 Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00