327 Linear courses

This course equips learners with a comprehensive understanding of the NumPy stack, including NumPy, Matplotlib, Pandas, and SciPy, to effectively tackle common challenges in deep learning and data science. Master the basics with this carefully structured course.

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 and learn from the experts with this step-by-step

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

5G training course description This course is designed to give the delegate an understanding of the technologies and interworking requirements of the next generation of cellular communications. It is not a definitive set of descriptions but a possibility of the final deployment. During the course we will investigate the 10 pillars for 5G, which will include various Radio Access Technologies that are required to interwork smoothly. Hence we will look at the 4G Pro features and other RATs. What will you learn List the ten pillars of 5G deployment. Explain the 5G Internet and Software Distributed Networks (SDN). Explain carrier aggregation, the mobile cloud and RAT virtualisation. Explain an overall picture of 5G architecture. 5G training course details Who will benefit: Anyone who is looking to work with next generation networks. Prerequisites: Mobile communications demystified Duration 3 days 5G training course contents Drivers for 5G 5G Road Map, 10 Pillars of 5G, evolving RATs, small cell, o SON, MTCm, mm-wave, backhaul, EE, new spectrum, spectrum sharing, RAN virtualisation. 4G LTE advanced features *MIMO, Downlink & uplink MIMO R8, MIMO technology in LTE advanced, Downlink 8-layer SU-MIMO, Downlink MU-MIMO, Uplink MU-MIMO, Uplink transmit diversity, Coordinated multi-point operation (CoMP), Independent eNB & remote base station configurations, Downlink CoMP, * Uplink Multi-Cell Reception. ICIC & eICIC ICIC, Homogeneous to heterogeneous network, eICIC, Macro-pico scenario, Macro-femto scenario, Time orthogonal frequencies. Almost Blank Subframe (ABS). Carrier aggregation Component carriers (CC), * CC aggregation, Intra-band contiguous solutions, Intra-band non-contiguous solutions, Inter-band non-contiguous solutions, CA bandwidth classes, Aggregated transmission bandwidth configurations (ATBC), Possible carrier aggregation configurations (Rel 9, 10 & 12). Enhanced Interference Mitigation & Traffic Adaptation (eIMTA) TDD UL-DL reconfiguration for traffic adaptation, Reconfiguration mechanisms, Interference mitigation schemes, Dynamic & flexible resource allocation. 5G architectures 5G in Europe, horizon 2020 framework, 5G infrastructure PPP, METIS project, innovation centre, 5G in North America, research, company R & D, 5G specifications. The 5G internet Cloud services, IoT & context awareness, network reconfiguration & virtualization support, hypervisors, SDN, the controller, service-oriented API, OpenFlow switches, SDN operation, SDN control for traffic flow redirection, OpenFlow controllers, how SDN works, application, control and infrastructure layers, a programmable network, how SDN & NFV tie together, SDN's downside, SDN orchestration, Mobility, architectures for distributed mobility management, MEDIEVAL & MEDIVO projects, a clean slate approach, mobility first architecture, network virtualization (VNet), INM, NetInf, ForMux, MEEM, GP & AM, QoS support, network resource provisioning, IntServ, RSVP, DiffServ, CoS, aggregated resource provisioning, SICAP, MARA, Emerging approach for resource over-provisioning, example use case architecture for the 5G internet, integrating SDN/NFV for efficient resource control, control information repository, service admission control policies, network resource provisioning, control enforcement functions, network configurations, network operations. Small cells for 5G Average spectral efficiency evolution, What are small cells? WiFi & Femto cells as candidate small-cell technologies, Capacity limits & achievable gains with densifications, gains with multi-antenna techniques, gains with small cells, Mobile data demand, approach & methodology, subscriber density projections, traffic demand projections, global mobile data traffic increase modelling, country level backhaul traffic projections, 2020 average spectrum requirement, Small cell challenges, backhaul, spectrum, automation. Cooperation for next generation wireless networks Cooperative diversity & relaying strategies, Cooperative ARQ & MAC protocols, NCCARQ & PRCSMA packet exchange, Physical layer impact on MAC protocol, NCCARQ overview, PHY layer impact, Performance evaluation, simulation scenario and results. Mobile clouds; technology & services for future communications platforms Mobile cloud, software, hardware and networking resources, Mobile cloud enablers, mobile user domain, wireless technologies, WWAN WLAN and WPAN range, Bluetooth, IEEE.802.15.4, software stacks, infrared, near field communications (NFC), store & forward vs compute & forward, random/linear network coding. Security for 5G communications Potential 5G architectures, Security issues & challenges in 5G, user equipment, mobile malware attacks, 5G mobile botnets, attacks on 4G networks, C-RNTI & packet sequence numbers based UE location tracking, false buffer status reports attacks, message insertion attacks, HeNB attacks, physical attacks, attacks on mobile operator's network, user data & identity attacks, DDoS attacks, amplification, HSS saturation, external IP networks.

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 Introduction Welcome to the course 00:02:00 Step 1: Pricing Policy and Pricing Objective 6 Steps of setting a Pricing policy 00:03:00 Different Pricing Objectives 00:07:00 Step 2: Estimating Demand Estimating Demand 00:07:00 Forms of Demand Curve 00:02:00 Excel: Estimating Linear Demand Curve 00:08:00 Excel: Estimating Power Demand curve with Elasticity2 00:05:00 Excel: Estimating Power Demand Curve with points2 00:03:00 Subjective Demand curve 00:01:00 Excel: Estimating Subjective Demand Curve2 00:02:00 Excel: Maximizing Revenue using Excel Solver 00:08:00 Step 3: Estimating Costs Estimating the cost function 00:05:00 Excel: Modeling Cost Function and Maximizing Profit 00:06:00 Including effect of complementary goods 00:01:00 Excel: Effect of complementary goods 00:05:00 Step 4: Analyzing competitors Analyzing Competitors 00:02:00 Step 5a : Price Bundling Strategy Price Bundling 00:07:00 Types of Bundling 00:08:00 The Bundling Problem 00:04:00 Excel: Solving Bundling problem Part 1 00:14:00 Excel: Solving Bundling problem Part 2 00:08:00 Excel: Solving Bundling problem (Price Reversal) 00:08:00 Step 5b: Non-Linear Pricing Strategies Non-Linear Pricing Strategies 00:03:00 Willingness to Pay of customers 00:03:00 Willingness to Pay of customers 00:03:00 Example Problem Statement 00:01:00 Excel: Standard Quantity Discounts 00:21:00 Excel: Two-Tier Pricing 00:04:00 Step 5c: Price Skimming Price Skimming Strategy 00:05:00 Excel: Price Skimming Strategy 00:10:00 Step 5d: Revenue Management Revenue Management 00:03:00 Excel: Handling Uncertainity 00:07:00 Appendix: Using Lookup functions 00:08:00 Appendix 1: Excel Crash Course Mathematical Formulas 00:19:00 Textual Formulas 00:17:00 Logical Formulas 00:11:00 Date-Time Formulas 00:07:00 Lookup Formulas ( V Lookup, Hlookup, Index-Match ) 00:08:00 Data Tools 00:19:00 Formatting Data And Tables 00:18:00 Pivot Tables 00:08:00 Excel Charts: Categories Of Messages That Can Be Conveyed 00:04:00 Elements Of Charts 00:05:00 The Easy Way Of Creating Charts 00:03:00 Bar And Column Charts 00:12:00 Congratulations 00:01:00 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

Get started with Neural networks and understand the underlying concepts of Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. This hands-on course will help you understand deep learning in detail with no prior coding or programming experience required.

Hawaiian Lomi Lomi (Temple Style) 1 Day Accredited Massage Diploma

Dive into the world of image segmentation with PyTorch. From tensors to UNet and FPN architectures, grasp the theory behind convolutional neural networks, loss functions, and evaluation metrics. Learn to mold data and tackle real-world projects, equipping developers and data scientists with versatile deep-learning skills.

Overview This comprehensive course on MATLAB Simulink for Electrical Power Engineering will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This MATLAB Simulink for Electrical Power Engineering comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this MATLAB Simulink for Electrical Power Engineering. It is available to all students, of all academic backgrounds. Requirements Our MATLAB Simulink for Electrical Power Engineering is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 8 sections • 47 lectures • 13:24:00 total length •Module 1- Solving One Non Linear Equation in MATLAB Using Fzero Function: 00:15:00 •Module 2-Example 1 on Solving Multiple Non Linear Equations in MATLAB Using Fsolve Function: 00:15:00 •Module 3- Example 2 on Solving Multiple Non Linear Equations in Matlab Using Fsolve: 00:13:00 •Module 4-Application Multi Level Inverter Part 1: 00:25:00 •Module 5- Application Multi Level Inverter Part 2: 00:05:00 •Module 1-Introduction to MATLAB Simulations Using Simulink: 00:04:00 •Module 2-Half Wave Uncontrolled Rectifier with R Load Principle of Operation: 00:21:00 •Module 3- Half Wave Controlled Rectifier R Load Principle of Operation: 00:05:00 •Module 4-Simulation of Half Wave Controlled Rectifier Using Simulink In Matlab: 00:26:00 •Module 5- Principle of Operation of Fully Controlled Bridge Rectifier Part 1: 00:06:00 •Module 6- Principle of Operation of Fully Controlled Bridge Rectifier Part 2: 00:06:00 •Module 7-Simulation of Bridge Controlled Rectifier: 00:16:00 •Module 8-AC Chopper with R Load Principle of Operation: 00:14:00 •Module 9- Simulation of AC Chopper with R and RL Loads in MATLAB: 00:11:00 •Module 10- Buck Regulator Principle of Operation Part 1: 00:16:00 •Module 11-Buck Regulator Principle of Operation Part 2: 00:17:00 •Module 12-Simulation of Buck Regulator in MATLAB: 00:14:00 •Module 13-Boost Regulator Principle of Operation: 00:23:00 •Module 14- Simulation of Boost Regulator in MATLAB: 00:12:00 •Module 15-Buck-Boost Regulator Principle of Operation: 00:17:00 •Module 16- Simulation of Buck-Boost Regulator: 00:09:00 •Module 17- Single Phase Half Bridge R-Load: 00:15:00 •Module 18- Single Phase Half Bridge RL-Load: 00:08:00 •Module 19-Simulation of Single Phase Half Bridge Inverter: 00:18:00 •Module 20-Single Phase Bridge Inverter R-Load: 00:06:00 •Module 21-Single Phase Bridge Inverter RL-Load: 00:07:00 •Module 22-Simulation of Single Phase Bridge Inverter: 00:10:00 •Module 23-Three Phase Inverters and Obtaining The Line Voltages: 00:15:00 •Module 24-Three Phase Inverters and Obtaining The Phase Voltages: 00:17:00 •Module 25-Simulation of Three Phase Inverter: 00:17:00 •Module 26-Simulation of Charging and Discharging Capacitor Using Matlab: 00:10:00 •Module 1-Separately Excited DC Machine: 00:21:00 •Module 2-DC Motor Modelling without Load Using Simulink in MATLAB: 00:25:00 •Module 3-DC Motor Modelling with Load Using Simulink in MALTAB: 00:23:00 •Module 4-DC Motor Block Simulation Using Power Library in MATLAB: 00:16:00 •Module 1-Construction and Principle of Operation of Synchronous Generator: 00:29:00 •Module 2-Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine: 00:29:00 •Module 3-Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine: 00:39:00 •Module 4-Simulation of Synchronous Machine Connected to Small Power System: 00:38:00 •Module 1-Construction and Theory of Operation of Induction Machines: 00:27:00 •Module 2-Equivalent Circuit and Power Flow in Induction Motor: 00:23:00 •Module 3-Torque-Speed Characteristics of Induction Motor: 00:20:00 •Module 4- Simulation of Induction Motor or Asynchronous Motor Using Simulink: 00:33:00 •Module 1- Importing Data from PSCAD Program for Fault Location Detection to MATLAB Program: 00:37:00 •Module 1-How to Implement PID Controller in Simulink of MATLAB: 00:14:00 •Module 2-Tuning a PID Controller In MATLAB Simulink: 00:17:00 •Assignment - MATLAB Simulink for Electrical Power Engineering: 00:00:00