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Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Internet of Things (IoT) Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Internet of Things (IoT) Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Internet of Things (IoT) Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Internet of Things (IoT) Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Internet of Things (IoT)? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Internet of Things (IoT) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Internet of Things (IoT) course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Internet of Things (IoT) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Internet of Things (IoT) 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Internet of Things (IoT) is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Agenda Module 01: Introduction 00:02:00 Module 02: Course Agenda 00:03:00 Unit 01: Introduction Module 01: Introduction to Internet of Things 00:13:00 Module 02: Choosing Cloud Services for IoT 00:05:00 Module 03: What is Raspberry Pi Part 1? 00:09:00 Module 04: What is Raspberry Pi Part 2? 00:06:00 Unit 02: Raspberry Pi Installation Module 01: Downloading OS for Raspberry Pi Noobs-Raspbian 00:07:00 Module 02: Install OS using NOOBS 00:11:00 Module 03: Remote Control of Raspberry Pi Using VNC Viewer 00:10:00 Module 04: Install OS using Raspbian Image part 1 00:06:00 Module 05: Install OS using Raspbian Image part 2 00:02:00 Unit 03: Getting Around Raspberry Pi Module 01: Getting Around Raspbian Operating System part 1 00:10:00 Module 02: Getting around Raspbian Operating System part 2 00:08:00 Module 03: Getting around Raspbian Operating System part 3 00:06:00 Module 04: How To Run Python program On Raspberry Pi 00:09:00 Unit 04: Raspberry Pi GPIO Output Module 01: Raspberry PI GPIO Concepts 00:07:00 Module 02: Raspberry Pi GPIO Interfacing Single LED 00:17:00 Module 03: Raspberry Pi GPIO Interfacing Multiple LED's 00:09:00 Module 04: Rapberry Pi GPIO Interfacing Buzzer 00:03:00 Unit 05: Output from Raspberry Pi Module 01: Raspberry Pi and Transistorized Switching 00:09:00 Module 02: Raspberry Pi and Relay part 1 00:13:00 Module 03: Raspberry Pi and Relay part 2 00:08:00 Unit 06: Inputs to Raspberry Pi Module 01: Accepting Digital Input on Raspberry Pi Part 1 00:13:00 Module 02: Accepting Digital Inputs on Raspberry Pi Part 2 00:07:00 Unit 07: Sensor Interfacing Module 01: Sensor Interfacing With Raspberry Pi LDR1 00:05:00 Module 02: Sensor Interfacing With Raspberry Pi LDR 2 00:10:00 Module 03: Sensor Interfacing With Raspberry Pi LDR 3 00:07:00 Module 04: Sensor Interfacing with Rapberry Pi DHTT11 part 1 00:10:00 Module 05: Sensor Interfacing with Rapberry Pi DHTT11 part 2 00:10:00 Module 06: Sensor Interfacing with Raspberry pi Using SenseHAT 00:11:00 Module 07: Ultrasonic Sensor Interfacing with Raspberry Pi 00:14:00 Unit 08: Interfacing of I2C Based BMP180 Sensor with Raspberry Pi Module 01: BMP180 with Raspberry Pi 00:07:00 Module 02: Enabling I2C on Raspberry Pi 00:05:00 Module 03: BMP180 Python Code 00:06:00 Unit 09: Internet of Things with Microsoft Azure Module 01: Getting Started With IoT 00:11:00 Module 02: Getting Started with Microsoft Azure IoT Hub Part 1 00:04:00 Module 03: Getting Started with Microsoft Azure IoT Hub Part 2 00:05:00 Module 04: Getting Started with Microsoft Azure IoT Hub Part 3 00:09:00 Module 05: Create Device inside Azure IoT Hub 00:06:00 Module 06: Enable Azure Cloud Shell and enable IoT Extension 00:08:00 Module 07: Send Data to Azure IoT Hub Using Python Program 00:09:00 Module 08: Send Actual Temperature and Humidity Values to Azure IoT hub 00:03:00 Module 09: Storing the Data on Microsoft Azure Using Custom Gateway 00:13:00 Module 10: Save data to blob storage using Stream Analytics Job 00:12:00 Module 11: Data Visualization with Power BI Part 1 00:07:00 Module 12: Data Visualization with Power BI Part 2 00:12:00 Module 13: Creating Custom web app with azure for data visualization Part 1 00:10:00 Module 14: Creating Custom web app with azure for data visualization Part 2 00:14:00 Module 15: Creating Custom web app with azure for data visualization Part 3 00:12:00 Module 16: Dealing with password error while pushing your webapp to azure 00:01:00 Module 17: Cleaning up Azure Resources 00:02:00 Module 18: Remote Monitoring using Azure Logic App Part 1 00:12:00 Module 19: Remote Monitoring using Azure Logic App Part 2 00:10:00 Unit 10: IoT with Thingspeak Module 01: Introduction to Thingspeak 00:06:00 Module 02: Create an account and send data to Thingspeak 00:08:00 Unit 11: Learn a new platform, Adafruit IO Module 01: Getting started with SaaS IoT Platform io.adafruit.com 00:08:00 Module 02: What is MQTT? 00:10:00 Module 03: Sending Data to Adafruit Io Using MQTT Part 1 00:17:00 Module 04: Sending Data to Adafruit io Using MQTT part 2 00:14:00 Module 05: Home automation project with adafruit IO Part 1 00:15:00 Module 06: Home Automation Project with Adafruit IO Part 2 00:02:00 Unit 12: IOT Security Module 01: IoT Security 00:14:00 Module 02: Conclusion 00:01:00 Assignment Assignment - Internet of Things (IoT) 00:00:00

Overview With the ever-increasing demand for Data Analysis in Microsoft Excel in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis in Microsoft Excel may be. Learning about Data Analysis in Microsoft Excel or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis in Microsoft Excel . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis in Microsoft Excel is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis in Microsoft Excel course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis in Microsoft Excel course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis in Microsoft Excel course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis in Microsoft Excel , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis in Microsoft Excel , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis in Microsoft Excel , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Data Analysis in Microsoft Excel course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module 1_ Introduction to Microsoft Excel Introduction to Microsoft Excel 00:00 Module 2_ Data Visualization and Advanced Functions Data Visualization and Advanced Functions 00:00 Module 3_ PivotTables and Regression PivotTables and Regression 00:00 Module 4_ Time Series Analysis in Excel Time Series Analysis in Excel 00:00

In today's data-driven world, 82% of businesses demand Data Science professionals - and they're willing to pay for it! With average global salaries of Data Scientists and Machine Learning experts surpassing $120,000 annually, it's clear: the future belongs to those who understand data. Our Advanced Diploma in Data Science & Machine Learning - Level 7 is meticulously designed to offer profound knowledge and skills . This Data Science & Machine Learning bundle encompasses a comprehensive selection, from the nuances of Statistics & Probability to the intriguing applications of Machine Learning in Flutter. Also, this comprehensive Data Science & Machine Learning bundle ensures you're well-equipped with the essential knowledge required in today's competitive global market. By opting for this Data Science & Machine Learning advanced diploma, you're not just learning - you're investing in a future filled with opportunities, lucrative incomes, and immense professional demand globally. Data Science & Machine Learning Course Learning Outcomes Grasp the fundamentals of Statistics & Probability. Acquire proficiency in Python for Data Science. Understand R programming in data analytics context. Dive deep into MySQL and its applications in Data Science. Master SQL techniques for Data Visualization and Analytics. Lay a strong foundation in basic machine learning concepts. Navigate through Azure Machine Learning and its utilities. This Data Science & Machine Learning bundle course, however, is designed to be your compass, guiding you through the intricacies of the most pivotal topics. With the Advanced Diploma, you delve deep into the mathematical bedrock of data science through Statistics & Probability. Python and R, the stalwarts of data programming, are unravelled, offering insights into their unique capabilities. SQL's unmatched prowess in data visualisation and analytics is highlighted, while Azure provides a window into the world of cloud-based machine learning. Lastly, understand the synergy of machine learning and mobile applications through Flutter. The benefits? A holistic understanding, positioning you ahead in the academic sphere and offering a competitive edge should you venture into research or further studies. Courses in this Data Science & Machine Learning bundle: Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 Data Science & Machine Learning with Python R Programming for Data Science Learn MySQL from Scratch for Data Science and Analytics SQL for Data Science, Data Analytics and Data Visualization Machine Learning Basics "Azure Machine Learning" Machine Learning use in Flutter, The Complete Guide Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the Data Science & Machine Learning course as proof of their achievement. You can order the endorsed certificate for only £129 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 Data Science & Machine Learning 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 Data Science & Machine Learning course has been reviewed and approved by the QLS and meets the highest quality standards. CPD 180 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Science & Machine Learning bundle is ideal for: Aspiring Data Scientists. Statisticians looking to expand into Machine Learning. Developers keen on integrating Machine Learning in apps. Research scholars in data-driven fields. Requirements To enrol in this Data Science & Machine Learning course, all you need is a basic understanding of the English Language and an internet connection. Career path Data Scientist Machine Learning Engineer Data Analyst SQL Database Administrator Research Scientist (Data Specialization) Flutter Developer with ML Integration Certificates 8 CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited Hard Copy Certificate Hard copy certificate - Included Delivery Charge: Inside the UK: £3.99 Outside the UK: £9.99 QLS Endorsed Hard Copy Certificate Hard copy certificate - Included Delivery Charge: Inside the UK: Free Outside the UK: £9.99 Other CPD Accredited Hard Copy Certificate Hard copy certificate - £9.99 Free Courses Hard Copy Certificates Are £9.99 Each. Delivery Charge: Inside the UK: Free Outside the UK: £9.99

The Real Estate Analyst course has been taught non-stop to global real estate firms over the last 25 years, and is without doubt the core financial modelling training in your career portfolio. Whether you have an upcoming financial modelling test for a new job or an APC exam, the Real Estate Analyst course is the choice for you.

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Advanced audio-visual learning modules of these Database Administrator courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once. Furthermore, to help you showcase your expertise in Database Administrator, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest. This Database Administrator Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Data Center Training Essentials: General Introduction Course 03: Data Analytics with Tableau Course 04: Basic Google Data Studio Course 05: Complete Google Analytics Course Course 06: Python for Data Analysis Course 07: Data Analysis in Excel Level 3 Course Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 09: GDPR Data Protection Level 5 Course 10: Level 3 Cyber Security Course 11: Encryption Course 12: Windows 10 Pro Complete Training Course 13: Functional Skills IT Course 14: Learning Computers and Internet Level 2 Benefits you'll get choosing Apex Learning: Pay once and get lifetime access to 14 CPD courses Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID for the title course included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules designed by expert instructors Learn at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Gain valuable knowledge without leaving your home 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 (For The Title Course) Hard Copy Certificate: Free (For The Title Course) The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Database Administrator expertise and essential knowledge, which will assist you in reaching your goal. Curriculum of Bundle Course 01: Introduction to Data Analysis Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding Course 02: Data Center Training Essentials: General Introduction Module 01: Data Center Introduction Module 02: Data Center Reliability Module 03: Data Center Equipment Module 04: Data Center White Space Module 05: Data Center Support Spaces Module 06: Data Center Security, Safety, Networks and IT Course 03: Data Analytics with Tableau Module 01: Introduction to the Course Module 02: Project 1: Discount Mart (Sales and Profit Analytics) Module 03: Project 2: Green Destinations (HR Analytics) Module 04: Project 3: Superstore (Sales Agent Tracker) Module 05: Northwind Trade (Shipping Analytics) Module 06: Project 5: Tesla (Stock Price Analytics) Module 07: Bonus: Introduction to Database Concepts Module 08: Tableau Stories Course 04: Basic Google Data Studio Module 01: Introduction to GDS Module 02: Data Visualization Module 03: Geo-visualization Module 04: A Socio-Economic Case Study Course 05: Complete Google Analytics Course Module 01: Overview Module 02: Navigation and Admin Module 03: Creating a New Google Analytics Account Module 04: Website Account Creation Module 05: Connecting To WordPress Website Module 06: Connecting To HTML Site Module 07: Connect Custom Page and Site Builders Module 08: Setting Up Annotations Module 09: Setting Up Intelligence Events Module 10: Set Up Custom Segments Module 11: Export Data for Analysis Module 12: Set Up Custom Reports Module 13: Set Up Google Integrations Module 14: Google Analytics Templates Module 15: Real Time Reporting Module 16: Setting Up Goals Module 17: Third Party Integrations Module 18: Audience Menu Overview Module 19: Interests and Geography Module 20: Conclusion Course 06: Python for Data Analysis Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 07: Data Analysis in Excel Level 3 Course Modifying a Worksheet Working with Lists Analyzing Data Visualizing Data with Charts Using PivotTables and PivotCharts Working with Multiple Worksheets and Workbooks Using Lookup Functions and Formula Auditing Automating Workbook Functionality Creating Sparklines and Mapping Data Forecasting Data Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Introduction Prepaid Expenses Models: Resources Download Accounting for Prepaid Expenses Excel Formulas Detailed: Introduction to three Excel Models Formula Based Prepaid Expenses Model Calculate Prepaid Expenses Amortisation from Exact Start Date Prepaid Expenses Summary with Power Query and Pivot Table Advanced VBA Prepaid Expenses Amortisation Model BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic Thankyou Course 09: GDPR Data Protection Level 5 Module 01: GDPR Basics Module 02: GDPR Explained Module 03: Lawful Basis for Preparation Module 04: Rights and Breaches Module 05: Responsibilities and Obligations Course 10: Level 3 Cyber Security FUNDAMENTALS OF NETWORKING GETTING STARTED WITH CYBER SECURITY LET'S BEGIN - THE FUNDAMENTALS OF CYBER SECURITY DIVING DEEP INTO CYBER SECURITY TYPES OF ACTORS, ATTACKS, MALWARE AND RESOURCES FIREWALLS AND ANTIVIRUS KEY SECURITY CONCEPTS Course 11: Encryption Section 01: Introduction Section 02: Basics of Common Encryption Section 03: Technical Aspects of Encryption Section 04: AES Basic Tech Demo Section 05: File and System Encryption Section 06: Conclusion Course 12: Windows 10 Pro Complete Training Module 01: Course Overview Module 02: Building Your Virtual Lab Environment Module 03: Upgrading Windows 7, 8, or 8.1 to Windows 10 Module 04: Building a Microsoft Server 2016 Domain Module 05: Windows Deployment Services (WDS) Module 06: Windows 10 Firewall, Windows Defender and UAC Module 07: Networking Module 08: Troubleshooting Module 09: User Preferences Module 10: Maintenance Course 13: Functional Skills IT Section 1: Introduction Section 2: Information Technology Section 3: Components of IT Section 4: Hardware Section 5: Operating System Section 6: Application/Software Section 7: Networking Section 8: Security Section 9: Traffic Flow & Enterprise Level IT Components Section 10: Storage Section 11: Database Section 12: Virtualisation & Cloud Section 13: Management & Other IT Jobs Course 14: Learning Computers and Internet Level 2 Module 01 : Computer Operating and Troubleshooting Module 02 : Internet and Computing - Key Applications Module 03 : Internet and Computing - Tools & Networking Module 04 : Windows 8 for PC Module 05 : Windows 10 - New Developments Module 06 : Cyber Security Awareness CPD 160 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Database Administrator bundle. Requirements Our Database Administrator course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. Career path Having this Database Administrator expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included P.S. The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

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Enrol on the now and start learning instantly! What You Get With The Internet of Things Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Internet of Things, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Course Agenda Module 01: Introduction 00:02:00 Module 02: Course Agenda 00:03:00 Unit 01: Introduction Module 01: Introduction to Internet of Things 00:13:00 Module 02: Choosing Cloud Services for IoT 00:05:00 Module 03: What is Raspberry Pi Part 1? 00:09:00 Module 04: What is Raspberry Pi Part 2? 00:06:00 Unit 02: Raspberry Pi Installation Module 01: Downloading OS for Raspberry Pi Noobs-Raspbian 00:07:00 Module 02: Install OS using NOOBS 00:11:00 Module 03: Remote Control of Raspberry Pi Using VNC Viewer 00:10:00 Module 04: Install OS using Raspbian Image part 1 00:06:00 Module 05: Install OS using Raspbian Image part 2 00:02:00 Unit 03: Getting Around Raspberry Pi Module 01: Getting Around Raspbian Operating System part 1 00:10:00 Module 02: Getting around Raspbian Operating System part 2 00:08:00 Module 03: Getting around Raspbian Operating System part 3 00:06:00 Module 04: How To Run Python program On Raspberry Pi 00:09:00 Unit 04: Raspberry Pi GPIO Output Module 01: Raspberry PI GPIO Concepts 00:07:00 Module 02: Raspberry Pi GPIO Interfacing Single LED 00:17:00 Module 03: Raspberry Pi GPIO Interfacing Multiple LED's 00:09:00 Module 04: Rapberry Pi GPIO Interfacing Buzzer 00:03:00 Unit 05: Output from Raspberry Pi Module 01: Raspberry Pi and Transistorized Switching 00:09:00 Module 02: Raspberry Pi and Relay part 1 00:13:00 Module 03: Raspberry Pi and Relay part 2 00:08:00 Unit 06: Inputs to Raspberry Pi Module 01: Accepting Digital Input on Raspberry Pi Part 1 00:13:00 Module 02: Accepting Digital Inputs on Raspberry Pi Part 2 00:07:00 Unit 07: Sensor Interfacing Module 01: Sensor Interfacing With Raspberry Pi LDR1 00:05:00 Module 02: Sensor Interfacing With Raspberry Pi LDR 2 00:10:00 Module 03: Sensor Interfacing With Raspberry Pi LDR 3 00:07:00 Module 04: Sensor Interfacing with Rapberry Pi DHTT11 part 1 00:10:00 Module 05: Sensor Interfacing with Rapberry Pi DHTT11 part 2 00:10:00 Module 06: Sensor Interfacing with Raspberry pi Using SenseHAT 00:11:00 Module 07: Ultrasonic Sensor Interfacing with Raspberry Pi 00:14:00 Unit 08: Interfacing of I2C Based BMP180 Sensor with Raspberry Pi Module 01: BMP180 with Raspberry Pi 00:07:00 Module 02: Enabling I2C on Raspberry Pi 00:05:00 Module 03: BMP180 Python Code 00:06:00 Unit 09: Internet of Things with Microsoft Azure Module 01: Getting Started With IoT 00:11:00 Module 02: Getting Started with Microsoft Azure IoT Hub Part 1 00:04:00 Module 03: Getting Started with Microsoft Azure IoT Hub Part 2 00:05:00 Module 04: Getting Started with Microsoft Azure IoT Hub Part 3 00:09:00 Module 05: Create Device inside Azure IoT Hub 00:06:00 Module 06: Enable Azure Cloud Shell and enable IoT Extension 00:08:00 Module 07: Send Data to Azure IoT Hub Using Python Program 00:09:00 Module 08: Send Actual Temperature and Humidity Values to Azure IoT hub 00:03:00 Module 09: Storing the Data on Microsoft Azure Using Custom Gateway 00:13:00 Module 10: Save data to blob storage using Stream Analytics Job 00:12:00 Module 11: Data Visualization with Power BI Part 1 00:07:00 Module 12: Data Visualization with Power BI Part 2 00:12:00 Module 13: Creating Custom web app with azure for data visualization Part 1 00:10:00 Module 14: Creating Custom web app with azure for data visualization Part 2 00:14:00 Module 15: Creating Custom web app with azure for data visualization Part 3 00:12:00 Module 16: Dealing with password error while pushing your webapp to azure 00:01:00 Module 17: Cleaning up Azure Resources 00:02:00 Module 18: Remote Monitoring using Azure Logic App Part 1 00:12:00 Module 19: Remote Monitoring using Azure Logic App Part 2 00:10:00 Unit 10: IoT with Thingspeak Module 01: Introduction to Thingspeak 00:06:00 Module 02: Create an account and send data to Thingspeak 00:08:00 Unit 11: Learn a new platform, Adafruit IO Module 01: Getting started with SaaS IoT Platform io.adafruit.com 00:08:00 Module 02: What is MQTT? 00:10:00 Module 03: Sending Data to Adafruit Io Using MQTT Part 1 00:17:00 Module 04: Sending Data to Adafruit io Using MQTT part 2 00:14:00 Module 05: Home automation project with adafruit IO Part 1 00:15:00 Module 06: Home Automation Project with Adafruit IO Part 2 00:02:00 Unit 12: IOT Security Module 01: IoT Security 00:14:00 Module 02: Conclusion 00:01:00 Resources Resources - Internet Of Things 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.