254 Probability courses

Management of Risk (M_o_R®) Foundation: In-House Training This M_o_R® Foundation course prepares learners to demonstrate knowledge and comprehension of the four elements of the M_o_R framework: Principles, Approach, Processes, Embedding and Reviewing and how these elements support corporate governance. The M_o_R Foundation Course is also a prerequisite for the M_o_R Practitioner qualification. What you will Learn At the end of the M_o_R Foundation course, participants will gain competencies in and be able to: Describe the key characteristics of risk and the benefits of risk management List the eight M_o_R Principles List and describe the use of the key M_o_R Approach documents Create Probability and Impact scales Define and distinguish between risks and issues Create a Risk Register Create a Stakeholder map Identify the key roles in risk management Use the key techniques and describe specialisms in risk management Undertake the M_o_R Foundation examination Introduction Introduction to the M_o_R course What is a risk? What is risk management? Why is risk management so important? Basic risk definitions The development of knowledge about risk management Corporate governance and internal control Where and when should risk management be applied? M_o_R Principles The purpose of M_o_R principles Aligns with objectives Fits the context Engages stakeholders Provides clear guidance Informs decision-making Facilitates continual improvement Creates a supportive culture Achieves measurable value Risk management maturity models M_o_R Approach Relationship between the documents Risk management policy Risk management process guide Risk management strategy Risk register Issue register Risk response plan Risk improvement plan Risk communications plan M_o_R Process Common process barriers Identify contexts Identify the risks Assess estimate Assess evaluate Plan Implement Communication throughout the process M_o_R Perspectives Strategic perspective Program perspective Project perspective Operational perspective Risk Specialisms Business continuity management Incident and crisis management Health and Safety management Financial risk management Environmental risk management Reputational risk management Contract risk management

Management of Risk (M_o_R®) Foundation: Virtual In-House Training This M_o_R® Foundation course prepares learners to demonstrate knowledge and comprehension of the four elements of the M_o_R framework: Principles, Approach, Processes, Embedding and Reviewing and how these elements support corporate governance. The M_o_R Foundation Course is also a prerequisite for the M_o_R Practitioner qualification. What you will Learn At the end of the M_o_R Foundation course, participants will gain competencies in and be able to: Describe the key characteristics of risk and the benefits of risk management List the eight M_o_R Principles List and describe the use of the key M_o_R Approach documents Create Probability and Impact scales Define and distinguish between risks and issues Create a Risk Register Create a Stakeholder map Identify the key roles in risk management Use the key techniques and describe specialisms in risk management Undertake the M_o_R Foundation examination Introduction Introduction to the M_o_R course What is a risk? What is risk management? Why is risk management so important? Basic risk definitions The development of knowledge about risk management Corporate governance and internal control Where and when should risk management be applied? M_o_R Principles The purpose of M_o_R principles Aligns with objectives Fits the context Engages stakeholders Provides clear guidance Informs decision-making Facilitates continual improvement Creates a supportive culture Achieves measurable value Risk management maturity models M_o_R Approach Relationship between the documents Risk management policy Risk management process guide Risk management strategy Risk register Issue register Risk response plan Risk improvement plan Risk communications plan M_o_R Process Common process barriers Identify contexts Identify the risks Assess estimate Assess evaluate Plan Implement Communication throughout the process M_o_R Perspectives Strategic perspective Program perspective Project perspective Operational perspective Risk Specialisms Business continuity management Incident and crisis management Health and Safety management Financial risk management Environmental risk management Reputational risk management Contract risk management

Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now Data analytics is a rapidly expanding discipline, and talented analysts are highly sought after in all industries. The UK and multinational organizations will undoubtedly see an increase in demand for skilled analysts in the coming years. We have created an 11-in-1 bundle course with a distinctive design to help you stand out in the related job market. It will guide you on how to read, evaluate, and display data in a way that is clear to all users and helps guide decisions. Along with this IT and Analytics course, you will get 10 premium courses, an original Hardcopy, 11 PDF Certificates (Main Course + Additional Courses) Student ID card as gifts. This Bundle Consists of the following Premium IT and Analytics courses: Course 01: Introduction to Data Analysis Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step Learning Outcomes Get an overview of data analysis. Familiarise yourself with the data science approach from the ground up. Learn the link between google data studio and data analytics. Explore various Excel data tools and management. Gain a better understanding of statistics and probability in terms of data science. Learn the fundamentals of Root cause analysis. Learn javascript and data visualization. Get introduced to the CSO-002. Get insight into electronic document management systems. Curriculum Course 01: Introduction to Data Analysis Introduction Agenda and Principles of Process Management The Voice of the Process Working as One Team for Improvement Exercise: The Voice of the Customer Tools for Data Analysis The Pareto Chart The Histogram The Run Chart Exercise: Presenting Performance Data Understanding Variation The Control Chart Control Chart Example Control Chart Special Cases Interpreting the Control Chart Control Chart Exercise Strategies to Deal with Variation Using Data to Drive Improvement A Structure for Performance Measurement Data Analysis Exercise Course Project Test your Understanding ---------- Other Courses Are ---------- Course 02: Quick Data Science Approach from Scratch Course 03: Excel Pivot Tables Course 04: Google Data Studio: Data Analytics Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines Course 06: Business Intelligence and Data Mining Masterclass Course 07: Statistics & Probability for Data Science & Machine Learning Course 08: RCA: Root Cause Analysis Course 09: Master JavaScript with Data Visualization Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002) Course 11: Electronic Document Management System Step How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone trying to get into the IT industry. Anyone who wants to better comprehend the role of IT and business analytics. Professionals who are looking to optimize business processes. Requirements 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. Career path This bundle course is a very engaging course and is proven to be beneficial to the many careers Certificates Certificate of completion Digital certificate - Included Certificate of completion is included in course price. Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Introduction to Data Analysis) absolutely Free! Other Hard Copy certificates are available for £10 each.

Developing the Business Case: Virtual In-House Training Business analysts must be able to create business case documents that highlight project benefits, costs, and risks. The business case is based on the real business need to be solved. These become parts of proposals, feasibility studies, and other decision support documents. This course teaches the purpose, structure, and content of a business case. It presents the basic techniques for determining financial ROI, non-tangible benefits, and the probability of meeting expectations. What you will Learn At the end of this program, you will be able to: Perform feasibility studies Justify the business investment to solve the business problem Prepare an effective business case document Plan and implement a business case approval process Foundation Concepts The role of the BA An introduction to the BABOK® Guide The business analyst and the product / project life cycle (PLC) The business case deliverable Introducing the Business Case Process The BA and strategy analysis The BA and the business case process (BCP) The BA during the business case process (BCP) The BA after the business case process (BCP) Importance of defining solution performance metrics Defining the Business Need Overview of defining the business need Business needs: problem / opportunity statement Product vision Objectives and constraints Exploring Business Case Solutions Overview of exploring solutions Solution identification for feasibility Solution definition for analysis Assessing project risks Justifying the Business Case Overview of justifying the business case Qualitative justification Quantitative justification Approving the Business Case Overview of business case approval Developing recommendations Preparing the decision package - documents Preparing the decision package - presentations

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Machine Learning Essentials with Python (TTML5506-P) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Mathematics is the universal language, bridging gaps, and solving mysteries of our daily lives. This Functional Skills Maths - Level 2 (Updated 2023) course has been carefully curated to elevate your mathematical understanding, offering clarity and depth on key concepts. From the world of fractions and percentages to the enigmatic arena of statistics and probability, every module ensures a robust conceptual foundation. Let's transform your approach to numbers and mathematical logic, making them allies in your quest for knowledge.

This PMI-RMP Certification Training will help you master the processes of risk management and the structured and objective approach to addressing uncertainty in projects. You will learn how to conduct risk planning, identification and analysis, and control both known and unknown risks in projects.

Telecomms training course description A comprehensive tour of the telecommunications technologies and terminology currently in use, and under development. What will you learn List and describe components of the PSTN. Explain how calls are made over the PSTN Compare analog and digital transmission methods. Describe the technologies within the transport plane. Recognise the benefits of extra features available in today's telephone networks. Telecomms training course details Who will benefit: Anyone new to the Telecommunications industry. Prerequisites: None. Duration 2 days Telecomms training course contents Telephone network architecture Handsets, local loop, distribution points, Local exchanges, main telephone switches, PBXs. Making a call - some basics Telephone call components, how a telephone call works, accessing the local exchange, loop disconnect, DTMF, standards, E.164, PSTN routing, Intelligent Networks, Special Rate Services. Analogue vs Digital Voice characteristics, PSTN bandwidth, analogue signalling, Digital encoding, PCM and the 64k, ADPCM and other voice compression methods. PBXs PABX, Call processing, networking PBXs, PBX facilities, bandwidth, blocking probability and Erlangs, Erlang models, using Erlang tables. Transmission methods Two wire transmission, 64k circuits, Nx64, E1, 2 wire to 4 wire conversion, echo, echo suppression, echo cancellers, twisted pair, coax, fibre optic, power lines, satellite systems, microwave. Signalling Analogue signalling, loop start, earth calling, E&M, AC15. Digital signalling -CAS, robbed bits and E1 slot 16 signalling. Digital signalling CCS, Q.931, SS7, Q.SIG, DPNSS, DASS2. Transport planes PDH, PDH issues, SDH, SDH architecture, SDH standards, SDH bit rates, SDH mulitplexors, DWDM. Networks Circuit Switched Networks, TDM, Packet Switched Networks, Frame Relay, Message Switching, Circuit Switching, STDM, Cell Switching, ATM, ATM cells, ATM traffic parameters, ATM QoS, MPLS. Other network access Modems, modulation, speeds, ISDN, BRI, PRI, xDSL, SDSL, ADSL. Other Services Centrex, VPNs, FeatureNet, CTI, Call Processing Systems, Voice Mail, Automated Attendant Systems, Interactive Voice Response, Call Management Systems, Call Conferencing, Star Services. Mobile communications 3 types of wireless telephone, mobile generations, base stations, cells, GSM, GPRS, 3G, UMTS, WCDMA, 4G, LTE. VoIP overview What is VoIP, VoIP benefits, What is IP? The IP header, Packetising voice, VoIP addressing, H.323, SIP, RTP. Bandwidth requirements.

Embark on an invigorating intellectual journey with this A-Level Maths course, meticulously crafted to imbibe the nuances of advanced mathematics. Delve into topics such as forces, probability, algebra, and vectors, honing your expertise while bolstering your critical thinking and analytical prowess. In the realm of UK education, A-levels stand as a testament to significant educational accomplishment. Our A-Level Maths course epitomises this, enhancing your appeal to both universities and employers while paving the way to a world of exciting opportunities. Adhering to the fresh AQA A-Level Maths syllabus, this online home study course is constructed to dovetail with your convenience, enabling you to learn at your own pace. Our comprehensive support system includes unlimited tutor assistance, a systematic induction, and well-structured assignments, preparing you efficiently for the exams. We ensure your access to our partnered exam centres for your final A-Level examinations. With our course, you'll have access to: Cutting-edge course content, shaped according to the latest specification. A Fast track option (for exams in 2022). A network of partnership exam centres. Unlimited tutor support and an exam pass guarantee. Awarding body: AQA Course code: X901 Qualification code: 7357 AQA qualifications enjoy international recognition, being taught in 30 countries and prized by employers and universities alike. These qualifications accommodate a wide range of abilities, encompassing GCSEs, IGCSEs, and A-levels. ⏱ Estimated Study Time Allocate between 300 and 360 hours for study, along with additional time for assignments. 👩‍🏫 Learning Methodology Our course is delivered via an immersive online learning platform, complete with diverse media resources like videos. However, if you prefer a more traditional approach, you can print the learning materials. 📆 Course Duration Enrol and benefit from our unlimited tutor support for up to 24 months. Upon enrolment, you will receive access to MyOxbridge, where all your learning materials are housed. 📋 Evaluation Examinations start from Summer 2022.  You will be evaluated on three written exams: Paper 1: 2 hours, 33.3% of A-Level, 100 marks. Paper 2: 2 hours, 33.3% of A-Level, 100 marks. Paper 3: 2 hours, 33.3% of A-Level, 100 marks. The exams will consist of a range of question types, from single-mark questions to multi-step problems. Our students are provided with a guaranteed exam space and an exam pass guarantee. Assignments The course includes several assignments. Though not contributing to your final grade, they allow you to receive feedback from your tutor, helping you track your progress. 👩‍🎓 Course Outcomes Upon successful course completion, you will receive an AQA-issued A-Level in Maths. This certificate mirrors those awarded to students at any other educational institution.  ℹ️ Further Details Difficulty - Level 3 Entry requirements - A GCSE or equivalent level in Mathematics is strongly advised. UCAS Points - 56 Course Content Core Content Mathematical argument, language, and proof Mathematical problem solving Mathematical modelling Proof Algebra and functions Coordinate geometry in the (x,y) plane Sequences and series Trigonometry Exponentials and logarithms Differentiation Integration Numerical methods Vectors Statistical sampling Data presentation and interpretation Probability Statistical distributions Statistical hypothesis testing Quantities and units in mechanics Kinematics Forces and Newton’s laws Moments

About this Virtual Instructor Led Training (VILT)  This 4 half-day Virtual Instructor Led Training (VILT) course will address a variety of contract and loan structuring issues associated with geothermal energy projects as well as comparison with solar, wind and battery storage. The course is designed to investigate how various project finance techniques and contract structures can be used to achieve a competitive power prices while maintaining a satisfactory equity return. Distinctive project finance features of power facilities that depend on geothermal, wind, hydro or solar resources will be evaluated with financial models. The course will cover economic analysis of exploration and development of geothermal facilities and how to incorporate probability of failure and success into an IRR framework. Subsequent sessions will address the theory underlying liquidated damages for delay, and performance as well as design of other incentives that is inherent in different contract structures. Nuanced project finance issues associated with structuring debt for renewable projects will be discussed including under what conditions the DSCR drives debt capacity and when the debt to capital ratio is instrumental. The course will be taught with a combination of theoretical discussions, term sheet review and focused financial models. Training Objectives Evaluation of the economic risks that arise from uncertainty associated with drilling exploration wells and development wells for geothermal projects. Analyse the theoretical issues with computing LCOE for geothermal projects compared to other renewable and non-renewable resources and the importance of cost of capital for renewable projects; Understand differences in contract structures for renewable projects and dispatchable projects and how a single price structure can distort incentives for efficient construction and operation; Understand components of financing that influence the bid price required to meet a required rate of return on equity and can result in relatively low prices with reasonable returns. Understand the importance of debt sizing constraints and what strategies are relevant when the debt to capital constraint applies relative to when the debt service coverage ratio drives the debt size; Understand how to compute P50, P90 and P99 for different projects driven by resource risk; Understand the difference between mean reverting resource variation and estimation mistakes that do not correct as the basis for 1-year P90 and 10-year P90. Understand under what conditions debt sculpting can affect returns and how synthetic sculpting can be used to increase returns when the DSCR constraint applies. Understand the theory of credit spreads, variable rate debt and interest rates in different currencies and compute the implied probability of default that in inherent in credit spreads. Understand how to evaluate the costs to equity investors and the benefits to lenders for various credit enhancements including DSRA accounts, cash flow sweeps and covenants. Course Level Basic or Foundation Training Methods The VILT will be delivered online in 4 sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day, including time for lectures, discussion, quizzes and short classroom exercises. Trainer Your expert course leader provides financial and economic consulting services to a variety of clients, he teaches professional development courses in an assortment of modelling topics (project finance, M&A, and energy). He is passionate about teaching in Africa, South America, Asia and Europe. Many of the unique analytical concepts and modelling techniques he has developed have arisen from discussion with participants in his courses. He has taught customized courses for MIT's Sloan Business School, Bank Paribas, Shell Oil, Society General, General Electric, HSBC, GDF Suez, Citibank, CIMB, Lind Lakers, Saudi Aramco and many other energy and industrial clients. His consulting activities include developing complex project finance, corporate and simulation models, providing expert testimony on financial and economic issues before energy regulatory agencies, and advisory services to support merger and acquisition projects. Our key course expert has written a textbook titled Corporate and Project Finance Modelling, Theory and Practice published by Wiley Finance. The book introduces unique modelling techniques that address many complex issues that are not typically used by even the most experienced financial analysts. For example, it describes how to build user-defined functions to solve circular logic without cumbersome copy and paste macros; how to write function that derives the ratio of EV/EBITDA accounting for asset life, historical growth, taxes, return on investment, and cost of capital; and how to efficiently solve many project finance issues related to debt structuring. He is in the process of writing a second book that describes a series of valuation and analytical mistakes made in finance. This book uses many case studies from Harvard Business School that were thought to represent effective business strategies and later turned into valuation nightmares. Over the course of his career our key course expert has been involved in formulating significant government policy related to electricity deregulation; he has prepared models and analyses for many clients around the world; he has evaluated energy purchasing decisions for many corporations; and, he has provided advice on corporate strategy. His projects include development of a biomass plant, analysis and advisory work for purchase of electricity generation, distribution and transmission assets by the City of Chicago, formulation of rate policy for major metro systems and street lighting networks, advocacy testimony on behalf of low income consumers, risk analysis for toll roads, and evaluation of solar and wind projects. He has constructed many advisory analyses for project finance and merger and acquisition transactions. Lastly, our key course expert was formerly Vice President at the First National Bank of Chicago where he directed analysis of energy loans and also created financial modelling techniques used in advisory projects. He received an MBA specializing in econometrics (with honours) from the University of Chicago and a BSc in Finance from the University of Illinois (with highest university honours). POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations