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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

Wireshark 101 training course description Wireshark is a free network protocol analyser. This hands-on course focuses on troubleshooting networks using the Wireshark protocol analyser. The course concentrates on the product and students will gain from the most from this course only if they already have a sound knowledge of the TCP/IP protocols What will you learn Download and install Wireshark. Capture and analyse packets with Wireshark. Configure capture and display filters. Customise Wireshark. Troubleshoot networks using Wireshark. Wireshark 101 training course details Who will benefit: Technical staff looking after networks. Prerequisites: TCP/IP Foundation for engineers Duration 2 days Wireshark 101 training course contents What is Wireshark? Protocol analysers, Wireshark features, versions, troubleshooting techniques with Wireshark. Installing Wireshark Downloading Wireshark, UNIX issues, Microsoft issues, the role of winpcap, promiscuous mode, installing Wireshark. Wireshark documentation and help. Hands on Downloading and installing Wireshark. Capturing traffic Starting and stopping basic packet captures, the packet list pane, packet details pane, packet bytes pane, interfaces, using Wireshark in a switched architecture. Hands on Capturing packets with Wireshark. Troubleshooting networks with Wireshark Common packet flows. Hands on Analysing a variety of problems with Wireshark. Capture filters Capture filter expressions, capture filter examples (host, port, network, protocol), primitives, combining primitives, payload matching. Hands on Configuring capture filters. Working with captured packets Live packet capture, saving to a file, capture file formats, reading capture files from other analysers, merging capture files, finding packets, going to a specific packet, display filters, display filter expressions. Hands on Saving captured data, configuring display filters. Analysis and statistics with Wireshark Enabling/disabling protocols, user specified decodes, following TCP streams, protocol statistics, conversation lists, endpoint lists, I/O graphs, protocol specific statistics. Hands on Using the analysis and statistics menus. Command line tools Tshark, capinfos, editcap, mergecap, text2pcap, idl2eth. Hands on Using tshark. Advanced issues 802.11 issues, management frames, monitor mode, packet reassembling, name resolution, customising Wireshark. Hands on Customising name resolution.

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Total NetFlow training course description A comprehensive hands on course covering NetFlow. The course starts with the basics of flows moving swiftly onto configuring NetFlow and studying the information it provides. What will you learn Describe NetFlow. Configure generators and collectors. Recognise how NetFlow can be used. Describe the issues in using NetFlow. Compare NetFlow with SNMP, RMON and sflow. Total NetFlow training course details Who will benefit: Technical staff working with NetFlow. Prerequisites: TCP/IP Foundation Duration 2 days Total NetFlow for engineers What is NetFlow? Flows. Where to monitor traffic. Hands on Wireshark flow analysis. Getting started with NetFlow NetFlow configuration. Hands on Accessing NetFlow data using the CLI. NetFlow architecture Generators and collectors. When flows are exported. NetFlow reporting products. SolarWinds. Hands on Collector software. NetFlow features and benefits Real time segment statistics, real time top talkers, traffic matrices. Hands on Traffic analysis with NetFlow. NetFlow issues NetFlow impact, agent resources, server resources, comparing NetFlow with SNMP, RMON and sflow. Hands on Advanced NetFlow configuration. Export formats Flow aging timers, NetFlow versions, export formats, templates, IPFIX. Hands on NetFlow packet analysis. NetFlow MIBs The NetFlow MIB, configuration, retrieving NetFlow statistics. Hands on Integrating NetFlow with SNMP.

WCNA training course description Wireshark is a free network protocol analyser. This hands-on course provides a comprehensive tour of using Wireshark to troubleshoot networks. The course concentrates on the information needed in order to pass the WCNA exam. Students will gain the most from this course only if they already have a sound knowledge of the TCP/IP protocols. What will you learn Analyse packets and protocols in detail. Troubleshoot networks using Wireshark. Find performance problems using Wireshark. Perform network forensics. WCNA training course details Who will benefit: Technical staff looking after networks. Prerequisites: TCP/IP Foundation for engineers Duration 5 days WCNA training course contents What is Wireshark? Network analysis, troubleshooting, network traffic flows. Hands on Download/install Wireshark. Wireshark introduction Capturing packets, libpcap, winpcap, airpcap. Dissectors and plugins. The menus. Right click. Hands on Using Wireshark. Capturing traffic Wireshark and switches and routers. Remote traffic capture. Hands on Capturing packets. Capture filters Applying, identifiers, qualifiers, protocols, addresses, byte values. File sets, ring buffers. Hands on Capture filters. Preferences Configuration folders. Global and personal configurations. Capture preferences, name resolution, protocol settings. Colouring traffic. Profiles. Hands on Customising Wireshark. Time Packet time, timestamps, packet arrival times, delays, traffic rates, packets sizes, overall bytes. Hands on Measuring high latency. Trace file statistics Protocols and applications, conversations, packet lengths, destinations, protocol usages, strams, flows. Hands on Wireshark statistics. Display filters Applying, clearing, expressions, right click, conversations, endpoints, protocols, combining filters, specific bytes, regex filters. Hands on Display traffic. Streams Traffic reassembly, UDP and TCP conversations, SSL. Hands on Recreating streams. Saving Filtered, marked and ranges. Hands on Export. TCP/IP Analysis The expert system. DNS, ARP, IPv4, IPv6, ICMP, UDP, TCP. Hands on Analysing traffic. IO rates and trends Basic graphs, Advanced IO graphs. Round Trip Time, throughput rates. Hands on Graphs. Application analysis DHCP, HTTP, FTP, SMTP. Hands on Analysing application traffic. WiFi Signal strength and interference, monitor mode and promiscuous mode. Data, management and control frames. Hands on WLAN traffic. VoIP Call flows, Jitter, packet loss. RTP, SIP. Hands on Playing back calls. Performance problems Baselining. High latency, arrival times, delta times. Hands on Identifying poor performance. Network forensics Host vs network forensics, unusual traffic patterns, detecting scans and sweeps, suspect traffic. Hands on Signatures. Command line tools Tshark, capinfos, editcap, mergecap, text2pcap, dumpcap. Hands on Command tools.

Total SIPp course description SIPp is a robust performance testing tool designed for evaluating the SIP protocol. This comprehensive course takes you on a journey from the initial installation of SIPp to mastering fundamental scenarios, exploring diverse architectures, delving into statistics analysis, and crafting XML scenario files. What will you learn Monitor SIP traffic with SIPp. Use SIPp for performance testing. Use the standard SIPp scenarios. Create custom scenarios in XML for SIPp. Total SIPp course details Who will benefit: Those working with SIP. Prerequisites: Definitive SIP for engineers Duration 2 days Total SIPp course contents Introduction What is SIPp? SIP review: UAC, UAS, INVITE, BYE. Sample SIP call flows. Hands on Wireshark, SIP call flow. Installing SIPp Getting SIPp, installing SIPp. Using SIPp Running sipp. sipp with uas scenario, sipp with uac scenario. The integrated scenarios. Online help. Hands on uac, uas. Controlling SIPp Hot keys, commands, UDP socket. Running SIPp in the background. Traffic control. SIPp performance testing. Hands on Changing call rates, remote control, pausing traffic. Monitoring SIP traffic Scenario screen, statistics. Response times, counters. Hands on Monitoring SIP traffic. More integrated scenarios SIPp and media and RTP. 3PCC. 3PCC extended. Transport modes: UDP, TCP, TLS, SCTP, IPv6 mono and multi socket. Hands on Third Party Call Control. XML What is XML? Content, markup, elements, attributes. Start tags, end tags. Hands on Displaying embedded scenarios, looking at the XML files of the integrated scenarios. Creating your own XML scenarios scenario, message commands, send, recv, nop, pause, sendCmd, recvCmd, common sipp scenario attributes, command specific sipp scenario attributes. XML DTD, jEdit. Hands on uac and uas scenario XML files. Recv actions Log and warning, exec, variables, variable types, variable scope. External variables. Hands on RTP streaming, Change a calls network destination, injection files. Regular expressions What is an RE. POSIX 1003.2. Re injection. Validation. Hands on regex example.

10 QLS Endorsed Courses for Data Scientist | 10 Endorsed Certificates Included | Life Time Access

Lean Six Sigma Green Belt Certification Program: In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Description Our comprehensive course combines " Accidents, Incidents, and Breakdowns and Vehicle Marshal and Banksman Training combines 2 aspects: Road safety measures to handle accidents, incidents, and breakdowns and essentials of critical health and safety responsibilities. Accidents, Incidents, and Breakdowns Training Content: Recognizing risks and potential incidents, including breakdowns, collisions, and other scenarios. Duty of care, taking preventative measures, and handling incidents. Understanding health and safety regulations and related statistics. Prevention strategies and appropriate responses in case of an incident. Personal safety and actions to be taken during a vehicle collision. Steps to follow when facing a breakdown, including monitoring gauges and risk assessments. Ensuring the safety of other road users and cooperating with emergency services and recovery operators. Handling bridge strikes, including prevention and actions in case of an incident. Vehicle Marshal and Banksman Learn critical health and safety responsibilities Maneuvering vehicles safely during loading and unloading operations The safe use of work equipment Best practices for guiding vehicles as a Banksman Join us to enhance your knowledge of road safety preparedness. Register today to ensure your drivers are well-versed in the rules of the road and equipped to handle unexpected challenges on their journeys. Please review our Terms and Conditions for more information.

CPD Accredited, Interactive Half Day Course Two courses to choose from, a 2 hour and a 3.5 hour course, both going into depth as to what dyslexia is, how it effect people as they're growing up, and how it effects them as adults. We also look at what specific strengths those with dyslexia have (dyslexic thinking), and how to help them in the workplace and daily life with the parts they struggle with. Course Contents: Statistics Causes of dyslexia What is dyslexia Co-morbidities The effects of dyslexia in childhood The effects of dyslexia in adulthood Strengths in people with dyslexia Supporting people with dyslexia