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Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Welcome to the course Introduction 00:02:00 Setting up R Studio and R crash course Installing R and R studio 00:05:00 Basics of R and R studio 00:10:00 Packages in R 00:10:00 Inputting data part 1: Inbuilt datasets of R 00:04:00 Inputting data part 2: Manual data entry 00:03:00 Inputting data part 3: Importing from CSV or Text files 00:06:00 Creating Barplots in R 00:13:00 Creating Histograms in R 00:06:00 Basics of Statistics Types of Data 00:04:00 Types of Statistics 00:02:00 Describing the data graphically 00:11:00 Measures of Centers 00:07:00 Measures of Dispersion 00:04:00 Introduction to Machine Learning Introduction to Machine Learning 00:16:00 Building a Machine Learning Model 00:08:00 Data Preprocessing for Regression Analysis Gathering Business Knowledge 00:03:00 Data Exploration 00:03:00 The Data and the Data Dictionary 00:07:00 Importing the dataset into R 00:03:00 Univariate Analysis and EDD 00:03:00 EDD in R 00:12:00 Outlier Treatment 00:04:00 Outlier Treatment in R 00:04:00 Missing Value imputation 00:03:00 Missing Value imputation in R 00:03:00 Seasonality in Data 00:03:00 Bi-variate Analysis and Variable Transformation 00:16:00 Variable transformation in R 00:09:00 Non Usable Variables 00:04:00 Dummy variable creation: Handling qualitative data 00:04:00 Dummy variable creation in R 00:05:00 Correlation Matrix and cause-effect relationship 00:10:00 Correlation Matrix in R 00:08:00 Linear Regression Model The problem statement 00:01:00 Basic equations and Ordinary Least Squared (OLS) method 00:08:00 Assessing Accuracy of predicted coefficients 00:14:00 Assessing Model Accuracy - RSE and R squared 00:07:00 Simple Linear Regression in R 00:07:00 Multiple Linear Regression 00:05:00 The F - statistic 00:08:00 Interpreting result for categorical Variable 00:05:00 Multiple Linear Regression in R 00:07:00 Test-Train split 00:09:00 Bias Variance trade-off 00:06:00 Test-Train Split in R 00:08:00 Regression models other than OLS Linear models other than OLS 00:04:00 Subset Selection techniques 00:11:00 Subset selection in R 00:07:00 Shrinkage methods - Ridge Regression and The Lasso 00:07:00 Ridge regression and Lasso in R 00:12:00 Classification Models: Data Preparation The Data and the Data Dictionary 00:08:00 Importing the dataset into R 00:03:00 EDD in R 00:11:00 Outlier Treatment in R 00:04:00 Missing Value imputation in R 00:03:00 Variable transformation in R 00:06:00 Dummy variable creation in R 00:05:00 The Three classification models Three Classifiers and the problem statement 00:03:00 Why can't we use Linear Regression? 00:04:00 Logistic Regression Logistic Regression 00:08:00 Training a Simple Logistic model in R 00:03:00 Results of Simple Logistic Regression 00:05:00 Logistic with multiple predictors 00:02:00 Training multiple predictor Logistic model in R 00:01:00 Confusion Matrix 00:03:00 Evaluating Model performance 00:07:00 Predicting probabilities, assigning classes and making Confusion Matrix in R 00:06:00 Linear Discriminant Analysis Linear Discriminant Analysis 00:09:00 Linear Discriminant Analysis in R 00:09:00 K-Nearest Neighbors Test-Train Split 00:09:00 Test-Train Split in R 00:08:00 K-Nearest Neighbors classifier 00:08:00 K-Nearest Neighbors in R 00:08:00 Comparing results from 3 models Understanding the results of classification models 00:06:00 Summary of the three models 00:04:00 Simple Decision Trees Basics of Decision Trees 00:10:00 Understanding a Regression Tree 00:10:00 The stopping criteria for controlling tree growth 00:03:00 The Data set for this part 00:03:00 Importing the Data set into R 00:06:00 Splitting Data into Test and Train Set in R 00:05:00 Building a Regression Tree in R 00:14:00 Pruning a tree 00:04:00 Pruning a Tree in R 00:09:00 Simple Classification Tree Classification Trees 00:06:00 The Data set for Classification problem 00:01:00 Building a classification Tree in R 00:09:00 Advantages and Disadvantages of Decision Trees 00:01:00 Ensemble technique 1 - Bagging Bagging 00:06:00 Bagging in R 00:06:00 Ensemble technique 2 - Random Forest Random Forest technique 00:04:00 Random Forest in R 00:04:00 Ensemble technique 3 - GBM, AdaBoost and XGBoost Boosting techniques 00:07:00 Gradient Boosting in R 00:07:00 AdaBoosting in R 00:09:00 XGBoosting in R 00:16:00 Maximum Margin Classifier Content flow 00:01:00 The Concept of a Hyperplane 00:05:00 Maximum Margin Classifier 00:03:00 Limitations of Maximum Margin Classifier 00:02:00 Support Vector Classifier Support Vector classifiers 00:10:00 Limitations of Support Vector Classifiers 00:01:00 Support Vector Machines Kernel Based Support Vector Machines 00:06:00 Creating Support Vector Machine Model in R The Data set for the Classification problem 00:01:00 Importing Data into R 00:08:00 Test-Train Split 00:09:00 Classification SVM model using Linear Kernel 00:16:00 Hyperparameter Tuning for Linear Kernel 00:06:00 Polynomial Kernel with Hyperparameter Tuning 00:10:00 Radial Kernel with Hyperparameter Tuning 00:06:00 The Data set for the Regression problem 00:03:00 SVM based Regression Model in R 00:11:00 Assessment Assessment - Machine Learning Masterclass 00:10:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Network+ training course description This network+ course covers the TCP/IP side of the exam. For delegates to pass the exam it is important that they meet the prerequisites, self study is also required. An intensive hands on IP foundation. The course focuses on all parts of TCP/IP including layers 4 to 7 on end stations as well as layer 3 on routers. The TCP/IP protocols are also studied to enable delegates to be able to troubleshoot TCP/IP using Wireshark. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Use ping, traceroute and other tools to diagnose faults on a network. Configure IP on PCs and routers. Plan IP addresses and subnets. Analyse IP and TCP packets using an analyser. Troubleshoot TCP/IP. Network+ training course details Who will benefit: Those wishing to pass the Network+ exam. Prerequisites: Introduction to data communications & networking Duration 5 days Network+ training course contents What is TCP/IP? TCP and IP are protocols, 7 layer model, network layers, hardware/software layers, internetworking, protocols, What is IP? What is TCP? The internet, The IAB, RFCs. Ping and Wireshark Host configuration, IP addresses, subnet masks, default gateways, ping. Hands on Base configuration. Testing with ping. Analysing packets with Wireshark. Switches and Wireshark Switches versus hubs, layer 2 forwarding table, flooding, broadcasts. Hands on Building a switched based network. Configuring network devices Configuration options, console port, putty, telnet. Hands on Configuring switches, telnet. IP IP packet format, protocol field, TTL, DiffServ, fragments, ICMP. Hands on IP packet analysis. IP addressing 32 bits, dotted decimal, rules, networks, role of subnet masks, simple subnetting, prefix notation. Broadcasts, special use addresses. Hands on Planning and implementing addressing. IP and the lower layers ARP, media not supporting ARP. Hands on ARP. Routing What are routers? What routers do, default gateways, routing and addressing, routing tables, ways to update routing tables. Hands on Building a routed network, traceroute. Routing protocols IGPs and EGPs, RIP, RIPv2, Why not to use RIP, OSPF, OSPF metrics, convergence, distance vector protocols, link state protocols. Hands on OSPF, analysing routing tables, loopbacks. Network simulators Network simulators, EVE-NG, GNS3, CML. Hands on Using EVE-NG. Subnetting Subnetting to the bit level, ranges, how prefixes are used. Hands on Subnetting. VLANS and IP addressing What are VLANs, tagging, 802.1Q, Inter VLAN routing. Hands on Inter VLAN routing. TCP and UDP Layer 4, port numbers, client ports, broadcasts multicasts and layer 4, UDP header, TCP header, connections, ACK, sliding windows, options, connection states. Sockets. Hands on Analysing TCP packets. IPv4 address configuration Private addresses, NAT, NAPT, dynamic addressing, DHCP, link local addresses. Hands on DHCP, NAT. IPv6 What is IPv6, 128 bit addresses, address formats, IPv6 address allocation, header format, migration, dual stack, tunnelling, NAT64, DNS64. Hands on IPv6 setup troubleshooting. IPv6 address configuration Static addressing, EUI-64 addresses, IPv6 address order, SLAAC, DHCPv6. Hands on SLAAC. Applications Clients, servers, HTTP, Email, resource sharing, VoIP, video, terminal emulation, remote desktop. Network management and SNMP. Hands on Servers, TFTP, VoIP packet analysis. DNS Names and addresses, hosts file, how DNS works. FQDNs, DNS client configuration. Hands on Troubleshooting DNS. Security Firewalls, firewall architectures, DMZ, how firewalls work, proxy servers, filtering, ACLs, IDS, VPNs, authentication, encryption, tunnels, secure protocols. Hands on Firewalls, SSH Troubleshooting Methods, tools. Using the 7 layer model. Troubleshooting toolkits. Hands on Fixing the network.

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! 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? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.   Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:17:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method.: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00

LINX 1 training course description An intensive hands on IP foundation leading to LINX Accredited Internet Technician stage 1. The course focuses on all parts of TCP/IP including layers 4 to 7 on end stations as well as layer 3 on routers. The TCP/IP protocols are also studied to enable delegates to be able to troubleshoot TCP/IP using Wireshark. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. A multiple choice exam, leading to the LAIT I certification, is available after the course. The exam consists of 40 questions and lasts 1.5 hours. What will you learn Use ping, traceroute and other tools to diagnose faults on a network. Configure IP on PCs and routers. Plan IP addresses and subnets. Analyse IP and TCP packets using an analyser. Troubleshoot TCP/IP. LINX 1 training course details Who will benefit: Network engineers. Prerequisites: None. Duration 5 days LINX 1 training course contents What is TCP/IP? TCP and IP are protocols, 7 layer model, network layers, hardware/software layers, internetworking, protocols, What is IP? What is TCP? The internet, The IAB, RFCs. Ping and Wireshark Host configuration, IP addresses, subnet masks, default gateways, ping. Hands on Base configuration. Testing with ping. Analysing packets with Wireshark. Switches and Wireshark Switches versus hubs, layer 2 forwarding table, flooding, broadcasts. Hands on Building a switched based network. Configuring network devices Configuration options, console port, putty, telnet. Hands on Configuring switches, telnet. IP IP packet format, protocol field, TTL, DiffServ, fragments, ICMP. Hands on IP packet analysis. IP addressing 32 bits, dotted decimal, rules, networks, role of subnet masks, simple subnetting, prefix notation. Broadcasts, special use addresses. Hands on Planning and implementing addressing. IP and the lower layers ARP, media not supporting ARP. Hands on ARP. Routing What are routers? What routers do, default gateways, routing and addressing, routing tables, ways to update routing tables. Hands on Building a routed network, traceroute. Routing protocols IGPs and EGPs, RIP, RIPv2, Why not to use RIP, OSPF, OSPF metrics, convergence, distance vector protocols, link state protocols. Hands on OSPF, analysing routing tables, loopbacks. Network simulators Network simulators, EVE-NG, GNS3, CML. Hands on Using EVE-NG. Subnetting Subnetting to the bit level, ranges, how prefixes are used. Hands on Subnetting. VLANS and IP addressing What are VLANs, tagging, 802.1Q, Inter VLAN routing. Hands on Inter VLAN routing. TCP and UDP Layer 4, port numbers, client ports, broadcasts multicasts and layer 4, UDP header, TCP header, connections, ACK, sliding windows, options, connection states. Sockets. Hands on Analysing TCP packets. IPv4 address configuration Private addresses, NAT, NAPT, dynamic addressing, DHCP, link local addresses. Hands on DHCP, NAT. IPv6 What is IPv6, 128 bit addresses, address formats, IPv6 address allocation, header format, migration, dual stack, tunnelling, NAT64, DNS64. Hands on IPv6 setup troubleshooting. IPv6 address configuration Static addressing, EUI-64 addresses, IPv6 address order, SLAAC, DHCPv6. Hands on SLAAC. Applications Clients, servers, HTTP, Email, resource sharing, VoIP, video, terminal emulation, remote desktop. Network management and SNMP. Hands on Servers, TFTP, VoIP packet analysis. DNS Names and addresses, hosts file, how DNS works. FQDNs, DNS client configuration. Hands on Troubleshooting DNS. Security Firewalls, firewall architectures, DMZ, how firewalls work, proxy servers, filtering, ACLs, IDS, VPNs, authentication, encryption, tunnels, secure protocols. Hands on Firewalls, SSH Troubleshooting Methods, tools. Using the 7 layer model. Troubleshooting toolkits. Hands on Fixing the network.

Network fundamentals training course description An intensive hands on IP foundation leading to LINX Accredited Internet Technician stage 1. The course focuses on all parts of TCP/IP including layers 4 to 7 on end stations as well as layer 3 on routers. The TCP/IP protocols are also studied to enable delegates to be able to troubleshoot TCP/IP using Wireshark. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. A multiple choice exam, leading to the LAIT I certification, is available after the course. The exam consists of 40 questions and lasts 1.5 hours. What will you learn Use ping, traceroute and other tools to diagnose faults on a network. Configure IP on PCs and routers. Plan IP addresses and subnets. Analyse IP and TCP packets using an analyser. Troubleshoot TCP/IP. Network fundamentals training course details Who will benefit: Network engineers. Prerequisites: None Duration 5 days Network fundamentals training course contents What is TCP/IP? TCP and IP are protocols, 7 layer model, network layers, hardware/software layers, internetworking, protocols, What is IP? What is TCP? The internet, The IAB, RFCs. Ping and Wireshark Host configuration, IP addresses, subnet masks, default gateways, ping. Hands on Base configuration. Testing with ping. Analysing packets with Wireshark. Switches and Wireshark Switches versus hubs, layer 2 forwarding table, flooding, broadcasts. Hands on Building a switched based network. Configuring network devices Configuration options, console port, putty, telnet. Hands on Configuring switches, telnet. IP IP packet format, protocol field, TTL, DiffServ, fragments, ICMP. Hands on IP packet analysis. IP addressing 32 bits, dotted decimal, rules, networks, role of subnet masks, simple subnetting, prefix notation. Broadcasts, special use addresses. Hands on Planning and implementing addressing. IP and the lower layers ARP, media not supporting ARP. Hands on ARP. Routing What are routers? What routers do, default gateways, routing and addressing, routing tables, ways to update routing tables. Hands on Building a routed network, traceroute. Routing protocols IGPs and EGPs, RIP, RIPv2, Why not to use RIP, OSPF, OSPF metrics, convergence, distance vector protocols, link state protocols. Hands on OSPF, analysing routing tables, loopbacks. Network simulators Network simulators, EVE-NG, GNS3, CML. Hands on Using EVE-NG. Subnetting Subnetting to the bit level, ranges, how prefixes are used. Hands on Subnetting. VLANS and IP addressing What are VLANs, tagging, 802.1Q, Inter VLAN routing. Hands on Inter VLAN routing. TCP and UDP Layer 4, port numbers, client ports, broadcasts multicasts and layer 4, UDP header, TCP header, connections, ACK, sliding windows, options, connection states. Sockets. Hands on Analysing TCP packets. IPv4 address configuration Private addresses, NAT, NAPT, dynamic addressing, DHCP, link local addresses. Hands on DHCP, NAT. IPv6 What is IPv6, 128 bit addresses, address formats, IPv6 address allocation, header format, migration, dual stack, tunnelling, NAT64, DNS64. Hands on IPv6 setup troubleshooting. IPv6 address configuration Static addressing, EUI-64 addresses, IPv6 address order, SLAAC, DHCPv6. Hands on SLAAC. Applications Clients, servers, HTTP, Email, resource sharing, VoIP, video, terminal emulation, remote desktop. Network management and SNMP. Hands on Servers, TFTP, VoIP packet analysis. DNS Names and addresses, hosts file, how DNS works. FQDNs, DNS client configuration. Hands on Troubleshooting DNS. Security Firewalls, firewall architectures, DMZ, how firewalls work, proxy servers, filtering, ACLs, IDS, VPNs, authentication, encryption, tunnels, secure protocols. Hands on Firewalls, SSH Troubleshooting Methods, tools. Using the 7 layer model. Troubleshooting toolkits. Hands on Fixing the network.

TCP/IP training course description An intensive hands on IP foundation leading to LINX Accredited Internet Technician stage 1. The course focuses on all parts of TCP/IP including layers 4 to 7 on end stations as well as layer 3 on routers. The TCP/IP protocols are also studied to enable delegates to be able to troubleshoot TCP/IP using Wireshark. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. A multiple choice exam, leading to the LAIT I certification, is available after the course. The exam consists of 40 questions and lasts 1.5 hours. What will you learn Use ping, traceroute and other tools to diagnose faults on a network. Configure IP on PCs and routers. Plan IP addresses and subnets. Analyse IP and TCP packets using an analyser. Troubleshoot TCP/IP. TCP/IP training course details Who will benefit: Network engineers. Prerequisites: None Duration 5 days TCP/IP training course contents What is TCP/IP? TCP and IP are protocols, 7 layer model, network layers, hardware/software layers, internetworking, protocols, What is IP? What is TCP? The internet, The IAB, RFCs. Ping and Wireshark Host configuration, IP addresses, subnet masks, default gateways, ping. Hands on Base configuration. Testing with ping. Analysing packets with Wireshark. Switches and Wireshark Switches versus hubs, layer 2 forwarding table, flooding, broadcasts. Hands on Building a switched based network. Configuring network devices Configuration options, console port, putty, telnet. Hands on Configuring switches, telnet. IP IP packet format, protocol field, TTL, DiffServ, fragments, ICMP. Hands on IP packet analysis. IP addressing 32 bits, dotted decimal, rules, networks, role of subnet masks, simple subnetting, prefix notation. Broadcasts, special use addresses. Hands on Planning and implementing addressing. IP and the lower layers ARP, media not supporting ARP. Hands on ARP. Routing What are routers? What routers do, default gateways, routing and addressing, routing tables, ways to update routing tables. Hands on Building a routed network, traceroute. Routing protocols IGPs and EGPs, RIP, RIPv2, Why not to use RIP, OSPF, OSPF metrics, convergence, distance vector protocols, link state protocols. Hands on OSPF, analysing routing tables, loopbacks. Network simulators Network simulators, EVE-NG, GNS3, CML. Hands on Using EVE-NG. Subnetting Subnetting to the bit level, ranges, how prefixes are used. Hands on Subnetting. VLANS and IP addressing What are VLANs, tagging, 802.1Q, Inter VLAN routing. Hands on Inter VLAN routing. TCP and UDP Layer 4, port numbers, client ports, broadcasts multicasts and layer 4, UDP header, TCP header, connections, ACK, sliding windows, options, connection states. Sockets. Hands on Analysing TCP packets. IPv4 address configuration Private addresses, NAT, NAPT, dynamic addressing, DHCP, link local addresses. Hands on DHCP, NAT. IPv6 What is IPv6, 128 bit addresses, address formats, IPv6 address allocation, header format, migration, dual stack, tunnelling, NAT64, DNS64. Hands on IPv6 setup troubleshooting. IPv6 address configuration Static addressing, EUI-64 addresses, IPv6 address order, SLAAC, DHCPv6. Hands on SLAAC. Applications Clients, servers, HTTP, Email, resource sharing, VoIP, video, terminal emulation, remote desktop. Network management and SNMP. Hands on Servers, TFTP, VoIP packet analysis. DNS Names and addresses, hosts file, how DNS works. FQDNs, DNS client configuration. Hands on Troubleshooting DNS. Security Firewalls, firewall architectures, DMZ, how firewalls work, proxy servers, filtering, ACLs, IDS, VPNs, authentication, encryption, tunnels, secure protocols. Hands on Firewalls, SSH Troubleshooting Methods, tools. Using the 7 layer model. Troubleshooting toolkits. Hands on Fixing the network.

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Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Data Science Overview 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 R and RStudio Engine and Coding Environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A Quick Tour 00:04:00 Introduction to Basics Arithmetic With R 00:03:00 Variable Assignment 00:04:00 Basic data types in R 00:03:00 Vectors Creating a Vector 00:05:00 Naming a Vector 00:04:00 Arithmetic Calculations On Vectors 00:07:00 Vector selection 00:06:00 Selection By Comparison 00:04:00 Matrices 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 Factors What is Factor 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Data Frames What's a Data Frame 00:03:00 Creating a Data Frame 00:04:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Lists Why Would You Need Lists 00:01:00 Creating Lists 00:03:00 Selecting Elements From a List 00:03:00 Adding more data to the list 00:02:00 Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Logical Operators 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 Conditional Statements The IF Statement 00:04:00 IF…ELSE 00:03:00 The ELSEIF Statement 00:05:00 Full Exercise 00:03:00 Loops 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 00:03:00 For Loop With Conditionals 00:01:00 Using Next and Break With For Loop 00:03:00 Functions What is 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 R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different Ways To Load a Package 00:02:00 The Apply Family - Lapply 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 The Apply Family - Sapply & Vapply 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 Useful Functions Mathematical Functions 00:05:00 Data Utilities 00:08:00 Regular Expressions Grepl & Grep 00:04:00 Metacharacters 00:05:00 Sub & Gsub 00:02:00 More Metacharacters 00:04:00 Dates And Times 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 Getting and Cleaning Data Get and Set Current Directory 00:04:00 Get Data From the Web 00:04:00 Loading Flat Files 00:05:00 Loading Excel files 00:03:00 Plotting Data in R 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 Data Manipulation With dplyr 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 Ccomponent: 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 Supplementary Resources Supplementary Resources - Learning R Programming for Data Science 00:00:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00