250 Matrix courses delivered Online

Want to become an expert NLP engineer and a data scientist? Then this is the right course for you. In this course, we will be covering complex theory, algorithms, and coding libraries in a very simple way that can be easily grasped by any beginner as well.

Management of Value (MoV®) Practitioner: Virtual In-House Training This interactive MoV® Practitioner course provides a modular and case-study-driven approach to learning Management of Value (MoV). The core knowledge is structured and comprehensive; and well-rounded modules cover the methodology and various techniques. A case study is used to help appreciate the relevance of MoV in its practical application. What you will Learn The MoV Practitioner Course prepares you for the MoV Practitioner exam. Individuals certified at the MoV Practitioner level will be able to: Apply Management of Value (MoV) principles, processes and techniques, and advocate the benefits of this application appropriately to the senior Management. Develop a plan of MoV activities for the whole lifecycle of small and large projects and programs. Plan an MoV study, tailoring it to particular projects or programs and developing practical study or workshop handbooks as required. Understand and articulate value in relation to organizational objectives. Prioritize value drivers using function analysis and use these to demonstrate how value might be improved. Quantify monetary and non-monetary value using the Value Index, Value Metrics and the Value for Money ratio. Describe and comment on the application of various techniques relevant to MoV. Monitor improvements in value realized throughout a project lifecycle and capture learning which can be transferred to future projects. Offer suggestions and guidance about embedding MoV into an organization, including policy issues, undertake a health check, assess maturity and competence, and provide guidance on typical roles and responsibilities. Understand and articulate the use of MoV within other Best Management Practice methods and its contributions to them Benefits of Taking This Course Upon successful completion of this course, you will be able to: Organise and contribute constructively to a Management of Value (MoV) Study Demonstrate a knowledge of MoV principles, processes, approach, and environment Analyse a company, programme or project to establish its organisational value includes identification and weighting of Value Drivers Pass the AXELOS Practitioner Examination Function Analysis Customer FAST Diagram Value Tree Development Weighting Attributes Paired Comparisons Developing a Value Profile Developing a Value Index Value for Money Ratio Stimulating Innovation Value Engineering Option Evaluation and Selection Evaluation Matrix Value and Value for Money Timing and Planning Teams and Stakeholders MoV in the Organization Integrating with Best Management Practice Relationship between Process and Approach

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Graph Theory Basics is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Graph Theory Basics and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 10 hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Course Promo Graph Theory Promo 00:02:00 Module 01: Supplements Textbook Recommendations 00:02:00 Tools and Softwares 00:05:00 Sets 00:09:00 Number Sets 00:10:00 Parity 00:12:00 Terminologies 00:07:00 Module 02: Fundamentals Introduction 00:03:00 Graphs 00:11:00 Subgraphs 00:09:00 Degree 00:10:00 Sum of Degrees of Vertices Theorem 00:23:00 Adjacency and Incidence 00:09:00 Adjacency Matrix 00:16:00 Incidence Matrix 00:08:00 Isomorphism 00:08:00 Module 03: Paths Introduction 00:01:00 Walks, Trails, Paths, and Circuits 00:13:00 Examples 00:10:00 Eccentricity, Diameter, and Radius 00:07:00 Connectedness 00:20:00 Euler Trails and Circuits 00:18:00 Fleury's Algorithm 00:10:00 Hamiltonian Paths and Circuits 00:06:00 Ore's Theorem 00:14:00 Dirac's Theorem 00:06:00 The Shortest Path Problem 00:16:00 Module 04: Graph Types Introduction 00:01:00 Trivial, Null and Simple Graphs 00:10:00 Regular Graphs 00:10:00 Complete, Cycles and Cubic Graphs 00:10:00 Path, Wheel and Platonic Graphs 00:11:00 Bipartite Graphs 00:14:00 Module 05: Trees Introduction 00:01:00 Trees 00:14:00 Cayley's Theorem 00:03:00 Rooted Trees 00:10:00 Binary Trees 00:14:00 Binary Tree Traversals 00:18:00 Binary Expression Trees 00:09:00 Binary Search Trees 00:19:00 Spanning Trees 00:10:00 Forest 00:07:00 Module 06: Digraphs and Tournaments Introduction 00:01:00 Digraphs 00:12:00 Degree 00:09:00 Isomorphism 00:08:00 Adjacency Matrix 00:10:00 Incidence Matrix 00:05:00 Walks, Paths and Cycles 00:12:00 Connectedness 00:05:00 Tournaments 00:08:00 Module 07: Planar Graphs Introduction 00:01:00 Planar Graphs 00:10:00 Kuratowski's Theorem 00:14:00 Euler's Formula 00:10:00 Dual Graphs 00:11:00 Module 08: Graph Operations Introduction 00:01:00 Vertex and Edge Deletion & Addition 00:08:00 Cartesian Product 00:10:00 Graph Join and Transpose 00:04:00 Complement Graphs 00:05:00 Module 09: Graph Colourings Introduction 00:01:00 Vertex Colourings 00:05:00 Edge Colourings 00:09:00 Total Colourings 00:05:00

Performance management, Managing Performance, Employee engagement,

Embark on a journey into the world of strategic analysis with this advanced course. Delve deep into risk management standards, the COSO framework for internal controls, competitive positioning strategies, BCG Matrix for portfolio analysis, pricing strategies, and the impact of economies of scale. Equip yourself with the tools and models essential for navigating complex business landscapes. This course is a comprehensive exploration of advanced tools and models crucial for strategic analysis. After the successful completion of this course, you will be able to: ⦁ Understand risk management standards' significance and application for organizational resilience and threat mitigation. ⦁ Identify components of the COSO framework for effective internal controls and risk assessment. ⦁ Analyze different types of competitive positions to strategize for market advantage. ⦁ Comprehend BCG Matrix for product/service portfolio analysis. ⦁ Explore pricing strategies and their impact on revenue and market position. ⦁ Understand economies of scale and their influence on cost efficiency and competitiveness. Elevate your risk analysis expertise with our advanced course, meticulously curated for professionals. Uncover sophisticated tools and models designed for strategic precision, empowering you to navigate complexities with confidence. Sharpen your analytical prowess and stay ahead in the dynamic business landscape. Enroll to master the art of strategic risk analysis. Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Advanced Tools And Models For Strategic Analysis Self-paced pre-recorded learning content on this topic. Advanced Tools And Models For Strategic Analysis Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience.  1. Risk Management Professionals 2. Financial Analysts3. Strategic Planners4. Business Intelligence Analysts5. Project Managers6. Compliance Officers7. Data Scientists8. Decision Analysts Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

Duration 2 Days 12 CPD hours This course is intended for This class is intended for PMP?s looking to earn PDU's, or for Project Managers looking to learn more about Project Scope and Schedule Management techniques. This course provides participants with tools and techniques to help them determine and deliver products, services, and results that meet requirements, expectations, and deadlines. NOTE: This course will earn you 14 PDUs. 1 - PROJECT SCOPE AND TIME MANAGEMENT OVERVIEW Project Scope Management Overview Project Scope Mgt. Processes and Key Outputs Project Time Management Overview Project Time Mgt. Processes and Key Outputs Case Study Selection Requirements, Scope, and Negotiations 2 - PLAN SCOPE AND SCHEDULE MANAGEMENT Plan Scope and Schedule Mgt. Overview The Scope Management Plan The Requirements Management Plan The Schedule Management Plan 3 - COLLECT REQUIREMENTS Collect Requirements Overview Types of Requirements Effective Product/Solution Requirements Other Stakeholders and Requirements Collect Requirements Techniques Voice of the Customer Requirements Traceability Matrix 4 - DEFINE SCOPE Define Scope Overview Project Scope Statement Sections Create a Project Scope Statement 5 - CREATE WBS Create WBS Overview WBS by Deliverable WBS by Phase When to Subdivide a Work Package Further Effective WBSs General Process for Creating the WBS Create a WBS 6 - DEFINE ACTIVITIES Define Activities Overview Practical Considerations for Defining Activities Activities and Steps Milestones Create Activities and Milestones 7 - SEQUENCE ACTIVITIES Develop Schedule Overview Critical Path Resource Optimization ? Resource Leveling Resource Optimization ? Resource Smoothing Resolve Overallocations Critical Chain Schedule Compression Techniques 8 - ESTIMATE ACTIVITY RESOURCES Estimate Activity Resources Overview Resource Breakdown Structure Estimate Activity Resources Assign Resources to Activities 9 - ESTIMATE ACTIVITY DURATIONS Estimate Activity Durations Overview Expert Judgment Ratio Estimating Analogous Estimating Parametric Estimating Forecasting Three Point Estimating and PERT Estimating Reserves Estimate Activity Durations 10 - DEVELOP SCHEDULE Develop Schedule Overview Critical Path Resource Optimization ? Resource Leveling Resource Optimization ? Resource Smoothing Resolve Overallocations Critical Chain Schedule Compression Techniques 11 - VALIDATE SCOPE Validate Scope Overview Verify Scope Best Practices Create a Scope Validation Form 12 - CONTROL SCOPE AND SCHEDULE Control Scope Overview Control Schedule Overview Control Scope Best Practices Change Control Stakeholders Determine Change Control Stakeholders Change Control Process Change Request Form

Take your first step toward Natural Language Processing with this beginner-to-pro course. Gain an in-depth understanding of deep learning models for NLP with the help of examples. Learn the essential concepts from the absolute beginning with complete unraveling along with examples in Python.

The course is crafted to help you understand not only the role and impact of recommender systems in real-world applications but also provide hands-on experience in developing complete recommender systems engines for your customized dataset using projects. This learning-by-doing course will help you master the concepts and methodology of Python.

Overview This comprehensive course on R Programming for Data Science will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This R Programming for Data Science comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this R Programming for Data Science. It is available to all students, of all academic backgrounds. Requirements Our R Programming for Data Science is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 23 sections • 129 lectures • 06:25:00 total length •Introduction to Data Science: 00:01:00 •Data Science: Career of the Future: 00:04:00 •What is Data Science?: 00:02:00 •Data Science as a Process: 00:02:00 •Data Science Toolbox: 00:03:00 •Data Science Process Explained: 00:05:00 •What's Next?: 00:01:00 •Engine and coding environment: 00:03:00 •Installing R and RStudio: 00:04:00 •RStudio: A quick tour: 00:04:00 •Arithmetic with R: 00:03:00 •Variable assignment: 00:04:00 •Basic data types in R: 00:03:00 •Creating a vector: 00:05:00 •Naming a vector: 00:04:00 •Vector selection: 00:06:00 •Selection by comparison: 00:04:00 •What's a Matrix?: 00:02:00 •Analyzing Matrices: 00:03:00 •Naming a Matrix: 00:05:00 •Adding columns and rows to a matrix: 00:06:00 •Selection of matrix elements: 00:03:00 •Arithmetic with matrices: 00:07:00 •Additional Materials: 00:00:00 •What's a Factor?: 00:02:00 •Categorical Variables and Factor Levels: 00:04:00 •Summarizing a Factor: 00:01:00 •Ordered Factors: 00:05:00 •What's a Data Frame?: 00:03:00 •Creating Data Frames: 00:20:00 •Selection of Data Frame elements: 00:03:00 •Conditional selection: 00:03:00 •Sorting a Data Frame: 00:03:00 •Additional Materials: 00:00:00 •Why would you need lists?: 00:01:00 •Creating a List: 00:06:00 •Selecting elements from a list: 00:03:00 •Adding more data to the list: 00:02:00 •Additional Materials: 00:00:00 •Equality: 00:03:00 •Greater and Less Than: 00:03:00 •Compare Vectors: 00:03:00 •Compare Matrices: 00:02:00 •Additional Materials: 00:00:00 •AND, OR, NOT Operators: 00:04:00 •Logical operators with vectors and matrices: 00:04:00 •Reverse the result: (!): 00:01:00 •Relational and Logical Operators together: 00:06:00 •Additional Materials: 00:00:00 •The IF statement: 00:04:00 •IFELSE: 00:03:00 •The ELSEIF statement: 00:05:00 •Full Exercise: 00:03:00 •Additional Materials: 00:00:00 •Write a While loop: 00:04:00 •Looping with more conditions: 00:04:00 •Break: stop the While Loop: 00:04:00 •What's a For loop?: 00:02:00 •Loop over a vector: 00:02:00 •Loop over a list: 00:03:00 •Loop over a matrix: 00:04:00 •For loop with conditionals: 00:01:00 •Using Next and Break with For loop: 00:03:00 •Additional Materials: 00:00:00 •What is a Function?: 00:02:00 •Arguments matching: 00:03:00 •Required and Optional Arguments: 00:03:00 •Nested functions: 00:02:00 •Writing own functions: 00:03:00 •Functions with no arguments: 00:02:00 •Defining default arguments in functions: 00:04:00 •Function scoping: 00:02:00 •Control flow in functions: 00:03:00 •Additional Materials: 00:00:00 •Installing R Packages: 00:01:00 •Loading R Packages: 00:04:00 •Different ways to load a package: 00:02:00 •Additional Materials: 00:00:00 •What is lapply and when is used?: 00:04:00 •Use lapply with user-defined functions: 00:03:00 •lapply and anonymous functions: 00:01:00 •Use lapply with additional arguments: 00:04:00 •Additional Materials: 00:00:00 •What is sapply?: 00:02:00 •How to use sapply: 00:02:00 •sapply with your own function: 00:02:00 •sapply with a function returning a vector: 00:02:00 •When can't sapply simplify?: 00:02:00 •What is vapply and why is it used?: 00:04:00 •Additional Materials: 00:00:00 •Mathematical functions: 00:05:00 •Data Utilities: 00:08:00 •Additional Materials: 00:00:00 •grepl & grep: 00:04:00 •Metacharacters: 00:05:00 •sub & gsub: 00:02:00 •More metacharacters: 00:04:00 •Additional Materials: 00:00:00 •Today and Now: 00:02:00 •Create and format dates: 00:06:00 •Create and format times: 00:03:00 •Calculations with Dates: 00:03:00 •Calculations with Times: 00:07:00 •Additional Materials: 00:00:00 •Get and set current directory: 00:04:00 •Get data from the web: 00:04:00 •Loading flat files: 00:03:00 •Loading Excel files: 00:05:00 •Additional Materials: 00:00:00 •Base plotting system: 00:03:00 •Base plots: Histograms: 00:03:00 •Base plots: Scatterplots: 00:05:00 •Base plots: Regression Line: 00:03:00 •Base plots: Boxplot: 00:03:00 •Introduction to dplyr package: 00:04:00 •Using the pipe operator (%>%): 00:02:00 •Columns component: select(): 00:05:00 •Columns component: rename() and rename_with(): 00:02:00 •Columns component: mutate(): 00:02:00 •Columns component: relocate(): 00:02:00 •Rows component: filter(): 00:01:00 •Rows component: slice(): 00:04:00 •Rows component: arrange(): 00:01:00 •Rows component: rowwise(): 00:02:00 •Grouping of rows: summarise(): 00:03:00 •Grouping of rows: across(): 00:02:00 •COVID-19 Analysis Task: 00:08:00 •Additional Materials: 00:00:00 •Assignment - R Programming for Data Science: 00:00:00