39956 Courses

Learn how to use OneNote to create, organize and populate electronic notebooks. Course overview Duration: 4 hours OneNote is a digital notebook and can be a great way to easily take notes. Whether for meetings, on training courses or to help with to do lists. It works very much like it’s paper copy equivalent but, of course, with lots of enhanced features. Its integration with Outlook and the other office applications means you can easily take notes and link them to documents meeting details and then email them out. You can even add audio and video notes as reminders. Objectives  By the end of the course you will be able to: Create and manage notebooks Add contents Tag and prioritise content Create notes from other applications Create To Do Lists and integrate into Outlook Content Using OneNote Creating notebooks Creating sections and pages Formatting pages Using page templates Creating page templates Reordering sections and pages Deleting sections and pages Creating OneNote content Adding text Bullet lists Adding tables Adding images Adding drawings Adding links Adding audio and video notes Tagging Tagging Creating custom tags Creating to-do lists Searching and filtering for tags Notes Creating quick notes Filtering them in OneNote notebooks Linked notes Outlook integration Linking to tasks in Outlook Flagging notes for follow up Inserting Outlook meeting content Taking minutes Emailing OneNote pages Send emails to OneNote

This course provides the necessary knowledge, understanding and skills to persons who will knowingly disturb asbestos containing materials during the course of their work activities, including building maintenance workers and supervisory personnel, and building maintenance managers.

Duration 4 Days 24 CPD hours This course is intended for This is an introductory-level C++ programming course designed for developers with experience programming in C or other languages. Practical hands-on prior programming experience and knowledge is required. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with C++, 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: Writing procedural programs using C++ Using private, public and protected keywords to control access to class members Defining a class in C++ Writing constructors and destructors Writing classes with const and static class members Overloading operators Implementing polymorphic methods in programs Writing programs using file I/O and string streams Using manipulators and stream flags to format output Using the keyword template to write generic functions and classes Writing programs that use generic classes and functions Writing programs that use algorithms and containers of the Standard Library Apply object-oriented design techniques to real-world programming problems Using algorithms and containers of the Standard Library to manipulate string data Understand how C++ protects the programmer from implementation changes in other modules of an application Using try() blocks to trap exceptions Using catch() blocks to handle exceptions Defining exceptions and using throw to trigger them Introduction to C++ Programming / C++ Essentials is a skills-focused, hands-on C++ training course geared for experienced programmers who need to learn C++ coupled with sounds coding skills and best practices for OO development. Students will leave this course armed with the required skills to put foundation-level C++ programming skills right to work in a practical environment. The central concepts of C++ syntax and style are taught in the context of using object-oriented methods to achieve reusability, adaptability and reliability. Emphasis is placed on the features of C++ that support abstract data types, inheritance, and polymorphism. Students will learn to apply the process of data abstraction and class design. Practical aspects of C++ programming including efficiency, performance, testing, and reliability considerations are stressed throughout. Comprehensive hands on exercises are integrated throughout to reinforce learning and develop real competency Moving from C to C++ (Optional) New Compiler Directives Stream Console I/O Explicit Operators Standard Libraries Data Control Capabilities Handling Data New Declaration Features Initialization and Assignment Enumerated Types The bool Type Constant Storage Pointers to Constant Storage Constant Pointers References Constant Reference Arguments Volatile Data Global Data Functions Function Prototypes and Type Checking Default Function Data Types Function Overloading Problems with Function Overloading Name Resolution Promotions and Conversions Call by Value Reference Declarations Call-by-Reference and Reference Types References in Function Return Constant Argument Types Conversion of Parameters Using Default Initializers Providing Default Arguments Inline Functions Operator Overloading Advantages and Pitfalls of Overloading Member Operator Syntax and Examples Class Assignment Operators Class Equality Operators Non-Member Operator Overloading Member and Non-Member Operator Functions Operator Precedence This Pointer Overloading the Assignment Operator Overloading Caveats Creating and Using Objects Creating Automatic Objects Creating Dynamic Objects Calling Object Methods Constructors Initializing Member consts Initializer List Syntax Allocating Resources in Constructor Destructors Block and Function Scope File and Global Scope Class Scope Scope Resolution Operator :: Using Objects as Arguments Objects as Function Return Values Constant Methods Containment Relationships Dynamic Memory Management Advantages of Dynamic Memory Allocation Static, Automatic, and Heap Memory Free Store Allocation with new and delete Handling Memory Allocation Errors Controlling Object Creation Object Copying and Copy Constructor Automatic Copy Constructor Conversion Constructor Streaming I/O Streams and the iostream Library Built-in Stream Objects Stream Manipulators Stream Methods Input/Output Operators Character Input String Streams Formatted I/O File Stream I/O Overloading Stream Operators Persistent Objects Introduction to Object Concepts The Object Programming Paradigm Object-Orientated Programming Definitions Information Hiding and Encapsulation Separating Interface and Implementation Classes and Instances of Objects Overloaded Objects and Polymorphism Declaring and Defining Classes Components of a Class Class Structure Class Declaration Syntax Member Data Built-in Operations Constructors and Initialization Initialization vs. Assignment Class Type Members Member Functions and Member Accessibility Inline Member Functions Friend Functions Static Members Modifying Access with a Friend Class Templates Purpose of Template Classes Constants in Templates Templates and Inheritance Container Classes Use of Libraries Strings in C++ Character Strings The String Class Operators on Strings Member Functions of the String Class Inheritance Inheritance and Reuse Composition vs. Inheritance Inheritance: Centralized Code Inheritance: Maintenance and Revision Public, Private and Protected Members Redefining Behavior in Derived Classes Designing Extensible Software Systems Syntax for Public Inheritance Use of Common Pointers Constructors and Initialization Inherited Copy Constructors Destructors and Inheritance Public, Protected, Private Inheritance Exceptions Types of Exceptions Trapping and Handling Exceptions Triggering Exceptions Handling Memory Allocation Errors C++ Program Structure Organizing C++ Source Files Integrating C and C++ Projects Using C in C++ Reliability Considerations in C++ Projects Function Prototypes Strong Type Checking Constant Types C++ Access Control Techniques Polymorphism in C++ Definition of Polymorphism Calling Overridden Methods Upcasting Accessing Overridden Methods Virtual Methods and Dynamic Binding Virtual Destructors Abstract Base Classes and Pure Virtual Methods Multiple Inheritance Derivation from Multiple Base Classes Base Class Ambiguities Virtual Inheritance Virtual Base Classes Virtual Base Class Information The Standard Template Library STL Containers Parameters Used in Container Classes The Vector Class STL Algorithms Use of Libraries

The Safeguarding Vulnerable Adults: Communication in Care Course has been illustrated for vulnerable adults to teach the difference between neglect and abuse. It also makes them realise the importance of communication in care and sharing information and response. Start learning Safeguarding Vulnerable Adults: Communication in Care Course that will give you enough knowledge and skills to build your dream career. About this course This Safeguarding Vulnerable Adults: Communication in Care Course helps to grow your skills faster through the power of relevant content and world-class tutors. In this industry-leading bite-sized course, you will learn up-to-date knowledge in the relevant field within a few hours and get certified immediately. The modules of this course are very easy to understand and all of the topics are split into different sections. You will easily grasp and use the knowledge gained from this course in your career and go one step ahead of your competitors. The course is designed to improve your employability and provide you with the tools you need to succeed. Enrol today and start learning your essential skills. Why choose this course Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Get 24/7 help or advice from our email and live chat teams Get full tutor support on weekdays (Monday to Friday) Course Design The Safeguarding Vulnerable Adults: Communication in Care Course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Who Is This Course For:​ This Safeguarding Vulnerable Adults: Communication in Care Course is ideal for those who want to be skilled in this field or who wish to learn a new skill to build their dream career. If you want to gain extensive knowledge, potential experience, and be an expert in the related field then this is a great course for you to grow your career. Requirements This course is for anyone who would like to learn Safeguarding Vulnerable Adults: Communication in Care Course related skills to aid his/her career path. No formal entry prerequisites are required Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Course Content Module 1: Policy, Roles and Responsibilities for Safeguarding Vulnerable Adults Module 2: Abuse and Neglect Understanding Module 3: Learning the Importance of Communication in Care Module 4: Information Sharing and Responding to a Disclosure Module 5: Your Concern  Reporting Course Content Safeguarding Vulnerable Adults: Communication in Care Module 1: Policy, Roles and Responsibilities for Safeguarding Vulnerable Adults 00:14:00 Module 2: Abuse and Neglect Understanding 00:12:00 Module 3: Learning the Importance of Communication in Care 00:09:00 Module 4: Information Sharing and Responding to a Disclosure 00:19:00 Module 5: Your Concern Reporting 00:14:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

This course provides the theory, practical knowledge and skills required for use of microscopes and fibre counting to WHO rules, air sampling and four-stage clearance procedures. The course is based around 'HSG248 Asbestos: The Analysts Guide for Sampling, Analysis and Clearance Procedures'.

Start learning Construction Management Course: Cost Estimation that will give you enough knowledge and skills to build your dream career. About this course This Construction Management Course: Cost Estimation helps to grow your skills faster through the power of relevant content and world-class tutors. In this industry-leading bite-sized course, you will learn up-to-date knowledge in the relevant field within a few hours and get certified immediately. The modules of this course are very easy to understand and all of the topics are split into different sections. You will easily grasp and use the knowledge gained from this course in your career and go one step ahead of your competitors. The course is designed to improve your employability and provide you with the tools you need to succeed. Enrol today and start learning your essential skills. Why choose this course Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Get 24/7 help or advice from our email and live chat teams Get full tutor support on weekdays (Monday to Friday) Course Design The Construction Management Course: Cost Estimation is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Who Is This Course For:​ This Construction Management Course: Cost Estimation is ideal for those who want to be skilled in this field or who wish to learn a new skill to build their dream career. If you want to gain extensive knowledge, potential experience, and be an expert in the related field then this is a great course for you to grow your career. Requirements This course is for anyone who would like to learn Construction Management Course: Cost Estimation related skills to aid his/her career path. No formal entry prerequisites are required Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Course Content Module 01: Introduction to Construction Management Module 02: Role of Cost Estimator and New Aspects of Cost Estimation Module 03: Elements and Factors influencing Cost Estimation Module 04: Cost Estimation in Construction Industry Course Content Construction: Construction Cost Estimation Module 01: Introduction to Construction Management 00:08:00 Module 02: Role of Cost Estimator and New Aspects of Cost Estimation 00:07:00 Module 03: Elements and Factors influencing Cost Estimation 00:09:00 Module 04: Cost Estimation in Construction Industry. 00:25:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Investigate and recognise the role of project sponsor and the importance of the relationship between sponsor and project manager and how this can be improved. Course overview Duration: 1 day (6.5 hours) This workshop is designed to investigate, understand and develop the role of the project sponsor. By taking elements of effective governance from the guidance published by the APM (Association for Project Management) and Axelos Managing Successful Programmes, an improved project sponsor capability can be developed. The workshop will also explore the importance of the relationship between sponsor and project manager and how this can be improved. Whilst predominately designed for the project sponsor role, there is provision for a discussion with project manager representatives to agree an action plan to improve the delivery of projects within an organisation. Objectives  By the end of the course you will be able to: Describe and commit to the role of the Project Sponsor Identify the key principles of governance that can contribute to success Describe the environment in which the projects are delivered Explain the financial and resource constraints within the project environment Define the criteria used for project selection Identify the expectations of key stakeholders and develop a clear communication plan to engage with them Identify and resolve areas of conflict Describe the relationship with the Project Manager Create an effective environment and relationship for project success Content Introduction The Project Environment The Principles of Governance The background to the training Roles The Project Sponsor The Project Manager The Project Board Sponsor responsibilities Defining Project Selection Criteria and Prioritisation Business Case and Justification Finance and Funding Resourcing the projects Stakeholder Engagement Project Governance Resolving conflict between stakeholders Benefits Realisation Capitalising the lessons learned during project reviews Delivering success The relationship with the Project Manager and team Action Plan for the future The workshop will use case studies drawn from previous client projects, both successful and less successful.

Taking minutes is a much under-rated skill. It can be challenging at the best of times. So how do you do it for virtual meetings? This trainer-led session will help. It's a very practical programme which explores the issues specific to minuting on-line meetings and gives solutions to some of the trickier problems. Full of useful tips, the session will enable participants to: Identify how to adapt their current minute-taking skills to on-line meetings Plan and prepare for a meeting Follow a line of discussion Work in partnership with a remote Chair Deal confidently with minute-taking challenges. 1 Welcome Programme objectives Personal introductions 2 Adapting minute-taking to virtual meetings How is it different? What changes in approach are needed? 3 Preparation Preparing for the meeting Technology and equipment Dress and personal presentation Liaising with the Chair Practical preparation tips 4 Minuting tips Managing the 'techie' elements, eg. poor sound/visual quality Knowing who is speaking Following a line of discussion What if I don't hear or understand? Tips for producing a set of minutes 5 Session review Summary, key learning points, feedback and close

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm