This is ovberwriting?

[100% OFF] JavaScript, Bootstrap, & PHP - Certification for Beginners

A Comprehensive Guide for Beginners interested in learning JavaScript, Bootstrap, & PHP

[100% OFF] Data Science: Supervised Machine Learning Bootcamp in Python Free

This course focuses on one of the main branches of... More Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising the Python Libraries will train you enough and will make you comfortable with the programming language. The course is divided into two sections, in the first section, you will be having lectures about Python and the fundamental libraries like Numpy, Pandas, Seaborn, Scikit-Learn and Tensorflow that are necessary for one to be familiar with before putting his hands-on Supervised Machine Learning. Then is the Supervised Learning part, which basically comprises three main chapters Regression, Classification, and Deep Learning, each chapter is thoroughly explained, both theoretically and experimentally. During all of these lectures, we’ll be learning how to use the different machine learning algorithms to create some mind-blowing modules of Machine Learning, and at the end of the course, you’ll be trained enough that you would be able to develop you own Recognitions Systems and Prediction Models and many more. Let's get started! Who this course is for: Those who are interested in AI and Machine Learning Those who have basic knowledge of any programming language Those who want to be create awesome Machine Learning and AI modules And those who want to earn some handsome amount of money from Machine Learning Field in Future Less
Expired
156 used

[100% OFF] Complete Machine Learning with R Studio - ML for 2020 Free

You're looking for a complete Machine Learning cou... Morerse that can help you launch a flourishing career in the field of Data Science & Machine Learning, right? You've found the right Machine Learning course! After completing this course you will be able to: · Confidently build predictive Machine Learning models to solve business problems and create business strategy · Answer Machine Learning related interview questions · Participate and perform in online Data Analytics competitions such as Kaggle competitions Check out the table of contents below to see what all Machine Learning models you are going to learn. How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular techniques of machine learning. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through linear regression. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 3 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the Python environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in Python Understanding of models - Fifth and sixth section cover Classification models and with each theory lecture comes a corresponding practical lecture where we actually run each query with you. Why use R for Machine Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Less
Expired
75 used

[100% OFF] HTML, CSS and JavaScript: The Complete Web Developer Course Free

Do you need to master the art of front-end develop... Morement? Look no further. This course is your complete beginners guide to developing cutting-edge web pages that are fully mobile responsive. The course branches into three sections. 1. Explore HTML5 Learn the composition of a web page and how a web browser interprets html code to display the visual elements of a page. Learn the core fundamental aspects of HTML syntax, to ensure you are well prepared for the remaining sections ahead. 2. Explore CSS3 Learn to add stunning design elements to really make web pages visually aesthetic. Learn a broad range of CSS attributes to make web pages completely mobile responsive, even on the trickiest of devices such as phones and tablets. 3. Explore JavaScript Dive into adding interactive client-side functionality using JavaScript. JavaScript is an extremely powerful front-end programming language that can really help take web pages to another level. Learn how to add client-side validation to forms, animate images and objects, and manipulate both HTML and CSS. Who this course is for: Anyone who needs to learn to code Anyone who needs to build a website Less
Expires 21.08.2020
169 used, 100% success rate
Rate:

[100% OFF] Machine Learning with Jupyter Notebooks in Amazon AWS Free

Are you a company or a IT administrator, data cent... Moreer architect, consultant, enterprise architect, data protection officer, programmer, data security specialist, or big data analyst and want to gain fundamental and intermediate level skills and enjoy a fascinating high paying career? Or maybe you just want to learn additional tips and techniques taking to a whole new level? Welcome to Machine Learning, Reinforcement Learning and AWS course For Beginners - A one of its kind course! The flipped classroom model with hand-on learning will help you experience direct into the course as your begin your learning journey. Be sure to watch the preview lectures that set course expectations! In this course, you'll learn and practice: Machine Learning topics Jupyter Notebooks Reinforcement Learning Machine Learning Services in AWS AWS Sagemaker Dynamic Programming Q-Learning Understand best practices, and much more.... You will also get complete resources, toolkit, and code where applicable with this course! We've built this course with our Team ClayDesk of industry recognized developers and consultants to bring you the best of everything! So, if you would like to: - start your freelancing career and consult companies, this course is for you - gain marketable skills as an IT expert and professional, this course is for you - This course is not designed for advanced level students ...this Machine Learning, Reinforcement Learning and AWS course is exactly what you need, and more. (You’ll even get a certification of completion) See what our students say “It is such a solid course that covers all important areas of machine learning, and I now know hoe to predict future products based on their features. Simply awesome!.” - Alex Neuman “This is such an awesome course. I loved every bit of it – Wonderful learning experience!” Ankit Goring. Join thousands of other students and share valuable experience Why take this course? As an enterprise architect consulting with global companies, technology evangelist, and brand innovator, I have designed, created, and implemented enterprise level projects, I am excited to share my knowledge and transfer skills to my students. Enroll now in Machine Learning, Reinforcement Learning and AWS today and revolutionize your learning. Stay at the cutting edge of Machine Learning and Data Science —and enjoy bigger, brighter opportunities with AWS. Qasim Shah Who this course is for: Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game Anyone who is curios about machine learning Less
Expired
147 used

[100% OFF] Adobe Illustrator CC 2020 MasterClass Free

This course will help you learn the basics as well... More as advanced levels of concepts and applications in Adobe Illustrator CC 2020. It covers real world applications of: 1. Logo Design 2. Packaging Design & 3D Mock-Up 3. Typography and Color Theory 4. Social Media Posting Also, the tools of Adobe Illustrator have been thoroughly explained that will help you in creating the designs with much ease. Salient Features of this Course: A comprehensive course consisting of 179 video lectures that are organized in a pedagogical sequence. Detailed explanation of all tools and commands used in the course. Step-by-step instructions to guide the users through the learning process. Practice Test You will get a Certificate of Completion after completing the course. Less
Expired
72 used

[100% OFF] Learn Python Web Development With Flask Zero To Hero Free

Flask is a micro web framework written in Python. ... MoreIt is micro framework because it does not require dozens of tools and library. you can customize flask as you want with the help of flask and get creative with it. What will you learn? You will Learn about Back End Web Developed Flask Models Sqlalchemy Sqllite Python Advanced Databases Flask Login Login System Full CRUD functioning db Why Flask? Flask Make it easy to use and good for python beginners. it is best if you want to make project light weight Why this Course we will be making 2 different projects and 1 to work as assignment to do list app full blogging web app with login Project: Library Management System Who this course is for: Web Developers Beginners curious for python Beginners curious for python web development Beginners curious for python flask Beginners curious for python web frameworks Less
Expired
136 used

[100% OFF] Home Business Basic Sales & Marketing Tools

Learn About Some Of The Basic Sales & Marketin... Moreg Tools For A Home Business Less
Expired
61 used

[100% OFF] Azure Kubernetes Service - AKS Free

Learn how to create and manage Kubernetes using on... Moree of the leading managed services on the market. Azure Kubernetes Service Zero to Hero admin guide is an intermediate course which describes: Comparison of Managed vs self-managed Kubernetes solutions; Pros and Cons of Managed Kubernetes services; AKS Capacity Analysis; Detailed AKS network architecture; How to create an AKS cluster using Azure Portal and Azure CLI; Integrate AKS with Active Directory; Create Kubernetes users using self-signed certificates; How AKS creates and manages Azure storage resources; AKS monitoring and log debugging. Who this course is for: Fearless Kubernetes administrators. Less
Expired
104 used

[10$] Cloud Computing for Machine Learning

Build and Deploy Machine Learning programs on the cloud
Expired
104 used

[100% OFF] The Complete Guide Angular 8 for Java Developers 2020 Free

Angular is a TypeScript-based open-source front-en... Mored web application platform led by the Angular Team at Google and by a community of individuals and corporations to address all of the parts of the developer's workflow while building complex web applications. Angular is a complete rewrite from the same team that built AngularJS. Angular is a framework for building client applications in HTML and either JavaScript or a language like TypeScript that compiles to JavaScript. Angular combines declarative templates, dependency injection, end to end tooling, and integrated best practices to solve development challenges. Angular empowers developers to build applications that live on the web, mobile, or the desktop. This course is for existing Java developers who want to learn the popular Angular framework for developing front-end Web interfaces. In the course we cover all of the main principles of building websites in Angular, including the Typescript Language. This is taught with reference to Java and Java web technology examples, making it a very quick and easy way for Java developers to upgrade their skills to Angular. No prior knowledge of Javascript or Typescript is needed, although some basic HTML is useful. Who this course is for: web developers, .net developers, java developers, python developers Less
Expired
78 used

[100% OFF] The Art of Doing: Master Networks and Network Scanning

Go from entering "nmap 192.168.1.0/24" t... Moreo UNDERSTANDING the command Less
Expires 06.03.2021
98 used, 66% success rate
Rate:

[100% OFF] Learn Machine Learning From Scratch [May 2020 Edition] Free

The concept of Artificial Intelligence is used in ... Moresci-fiction movies to describe a virtual entity that crossed some critical threshold point and developed self-awareness. And like any good Hollywood movie, this entity will turn against humankind. OMG! It’s a great concept to fuel our basic survival fear. As you may guess, things, in reality, are completely different. Artificial Intelligence is one of the biggest revolutions in the software industry. It is a mind-shift on how to develop software applications. Instead of using hard-coded rules for performing something, we let the machines learn things from data, decipher the complex patterns automatically and then use it for multiple use cases. Who this course is for: Anyone Interested to learn Machine Learning Less
Expired
16 used

[100% OFF] Image Recognition using CNN: Keras & TensorFlow in R Studio Free

You're looking for a complete Convolutional Neural... More Network (CNN) course that teaches you everything you need to create a Image Recognition model in R, right? You've found the right Convolutional Neural Networks course! After completing this course you will be able to: Identify the Image Recognition problems which can be solved using CNN Models. Create CNN models in R using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts Have a clear understanding of Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc. How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Convolutional Neural networks course. If you are an Analyst or an ML scientist, or a student who wants to learn and apply Deep learning in Real world image recognition problems, this course will give you a solid base for that by teaching you some of the most advanced concepts of Deep Learning and their implementation in R without getting too Mathematical. Why should you choose this course? This course covers all the steps that one should take to create an image recognition model using Convolutional Neural Networks. Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 300,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Practice test, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems. Below are the course contents of this course on ANN: Part 1 (Section 2)- Setting up R and R Studio with R crash course This part gets you started with R. This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R. Part 2 (Section 3-6) - ANN Theoretical Concepts This part will give you a solid understanding of concepts involved in Neural Networks. In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model. Part 3 (Section 7-11) - Creating ANN model in R In this part you will learn how to create ANN models in R. We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. Lastly we learn how to save and restore models. We also understand the importance of libraries such as Keras and TensorFlow in this part. Part 4 (Section 12) - CNN Theoretical Concepts In this part you will learn about convolutional and pooling layers which are the building blocks of CNN models. In this section, we will start with the basic theory of convolutional layer, stride, filters and feature maps. We also explain how gray-scale images are different from colored images. Lastly we discuss pooling layer which bring computational efficiency in our model. Part 5 (Section 13-14) - Creating CNN model in R In this part you will learn how to create CNN models in R. We will take the same problem of recognizing fashion objects and apply CNN model to it. We will compare the performance of our CNN model with our ANN model and notice that the accuracy increases by 9-10% when we use CNN. However, this is not the end of it. We can further improve accuracy by using certain techniques which we explore in the next part. Part 6 (Section 15-18) - End-to-End Image Recognition project in R In this section we build a complete image recognition project on colored images. We take a Kaggle image recognition competition and build CNN model to solve it. With a simple model we achieve nearly 70% accuracy on test set. Then we learn concepts like Data Augmentation and Transfer Learning which help us improve accuracy level from 70% to nearly 97% (as good as the winners of that competition). By the end of this course, your confidence in creating a Convolutional Neural Network model in R will soar. You'll have a thorough understanding of how to use CNN to create predictive models and solve image recognition problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below are some popular FAQs of students who want to start their Deep learning journey- Why use R for Deep Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Deep learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Deep Learning journey Anyone curious to master image recognition from Beginner level in short span of time Less
Expired
56 used

[100% OFF] Python for beginners - Learn all the basics of python Free

Have you always wanted to learn programming but di... Moredn't know where to start ? Well now you are at the right place ! I created this python course to help everyone learn all the basics of this programming language. This course is really straight to the point and will give you all the notion about python. Also, the course is not that long so and the way the material is presented is very easy to assimilate. So if python is something that you are interested about, then you will definitely like this course. Enjoy your learning :) Who this course is for: People interested to learn how to program in python people curious about programming Less
Expired
73 used

[100% OFF] Search Engine Optimization for Websites - SEO Basics Free

This course will teach students every thing about ... MoreSEO in 40 minutes and make them perform SEO by using the best practices. What's more this SEO course is built to stand the test of time...keep reading to find out why! "Short and essential" "Really engaging, like the way you explain all the little things, good for us beginners!" "Struggled with these concepts before this course. Thank you for explaining it so simply" "Great course by a great instructor." Who this course is for: Students desiring to learn SEO People who want to perform on their websites to increase traffic Less
Expired
75 used

[100% OFF] CYBER SECURITY SPECIALIZATION : Part 1 Free

The growth in the technological field is exponenti... Moreal. Day by day, the IT sector is flourishing to a greater extent. With such rapid growth, the need for security is also increasing. People have started becoming concerned about their privacy. Cybersecurity issues are becoming a day-to-day struggle for businesses. Recent trends and cyber security statistics reveal a huge increase in hacked and breached data from sources that are common in the workplace. With these growing trends, every individual must be aware of security and that is why you should go for this course! Most of the people are often confused when they are asked - “WHAT IS CYBER SECURITY?” The most common reply is - “UM, HACKING. ” Well, hacking is part of cyber security but it really doesn’t mean that hacking is the synonym of cyber security. Many courses out there are only focusing on the practical approach of cyber security - HACKING. Well, hacking is not the only domain of cyber security. There are other domains also, for example Incident Response Team, Blue team, Security Audits, IT Security Management, Security laws and many more. In order to start practicing hacking, you should first know the concepts! You should understand how the world is dealing with cyber threats. HACKING is not the only “coolest” thing here. There are other security topics as well. !!!! Hackers attack every 39 seconds, on average 2,244 times a day. !!!! So are you sure that your data is well protected from these hackers? Have you even configured your network to maintain your privacy? Do you know how hackers can gain access to your devices without you even getting notified? Well, don’t worry! We are here to answer these questions. There might be many questions in your mind regarding this course. We will surely address all of them once you enroll for this course, but for the time being, we’ll focus on the following questions: WHY SHOULD I LEARN CYBER SECURITY? Let’s face it. We live in a digital world. Our work lives, personal lives, and finances have all begun gravitating toward the world of the internet, mobile computing, and electronic media. Unfortunately, this widespread phenomenon makes us more vulnerable than ever to malicious attacks, invasions of privacy, fraud, and other such frightening cases. That’s why cyber security is such a vital part of a secure and well-ordered digital world. Cybersecurity keeps us safe from hackers, cyber criminals, and other agents of fraud. But let me ask you a question, HOW GOOD IS YOUR KNOWLEDGE ABOUT CYBER SECURITY? Here are some facts that would blow up your mind! According to Varonis, Worldwide spending on cyber security is forecasted to reach $133.7 billion in 2022. Data breaches exposed 4.1 billion records in the first half of 2019. Symantec says, the top malicious email attachment types are .doc and .dot which make up 37%, the next highest is .exe at 19.5% These are not just facts but they are warnings! Everyone who is accessing a device should be aware of their security and that is why we have designed this course. Okay, here comes the next question. UM, OKAY! BUT WHY SHOULD I ENROLL FOR THIS COURSE? The perfect answer to this question would be - Have a look at our curriculum. THE FUNDAMENTALS OF CYBER SECURITY, is the first part of our CYBER SECURITY SPECIALIZATION. In this course, we have covered right from the basics of computer networking to the advance concepts such as cryptography, security auditing, incident management. Yes, we have actually started from the definition of a Computer Network. Our course is broadly divided into seven sections. In the first section we have covered the basics of networking. We have discussed different protocols and their usage. We have talked about IP addresses and their classes and a lot of things which are important from the point of view of cyber security. Bonus Material - We have included practicals also! From the second section we are actually talking about cyber security. Right from the history of cyber security to different terminologies have been discussed in this section. We have designed the curriculum in such a way that even a novice can understand cyber security and we are so sure that this course would actually give a better idea of cyber security. You will learn about critical thinking and its importance to pursue a career in Cyber security. You will also learn about organizations and resources to further research cyber security issues in the Modern era. This course is intended for anyone who wants to gain a basic understanding of Cyber security or as the first course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst. We recommend you to watch our introductory video where we have discussed the entire syllabus :) Have a look at few highlights from our course. Handpicked curriculum, specially designed for all levels of learners. Continuous assessment through challenging quizzes Get your questions answered within 48 hours A variety of resources such as useful links, books, PDFs are also provided Regular updates related to cyber security Exploration of different aspects of Cybersecurity Practicals are also included along with theory You will understand how cryptography works in real life Concepts such as firewalls, antivirus, cyber attacks are also discussed and Many more. We encourage suggestions WHO CAN ENROLL FOR THIS COURSE? This course is not intended for a specific group of people. Anyone who wants to learn about cyber security can enroll for this course. If you already know about security, you can always revisit the ideas and clear your doubts if you have any. We have not only covered the technical topics but also included all the statistics as well. For example we have discussed the scope of cyber security along with the career insights and also the salaries of different job roles in this field. This course will help you to decide whether you want to become a Penetration tester or security auditor or Red Team Specialist. In short, this is the perfect course if you want to kick start your career in cyber security! BOTTOM LINE - Once you move ahead in this course, you will get a clear idea about cyber sec. The way we have put all the things together helps the learner in creating an interest in this field. We would like to assure one thing to you - THIS COURSE WILL LITERALLY TELL YOU EVERYTHING ABOUT CYBER SECURITY. Happy Learning! Less
Expired
96 used

[100% OFF] Oracle SQL : Practical Examples : Go from Beginner to Master Free

***SQL course which gained immediate popularity wi... Moreth the launch on UDEMY*** ============================================================================ ***Continuously being updated with new topics/videos every week*** ***Added lecture SQL vs NOSQL*** > 19 Dec 2019 (under Interview Section) ***Added Interview Section*** > 15 Dec 2019 *** Added lecture Most Important SQL Queries*** > 15 Dec 2019 ***Added lecture What is VIEW?*** > 15 Dec 2019 ============================================================================= You need to learn the most important and powerful language of the database world - SQL which makes your programming skills complete and enriched in just less than 20 hours of study! If you have already wasted your time and money in hunting for a complete yet concise course in SQL through random youtube videos or offered by inexperienced people - then you are at the right place here. This course brings step-by-step lessons in its logical series of videos to help you master the art and science of SQL. Moreover there is not even a basic knowledge of programming envisaged while designing this course. This course has been brought by an highly experienced faculty who have had 20+ years of experience in working as Oracle developer and DBA out of which 6 years onside in USA and UK. The faculty has been working in Oracle field ranging from Oracle version 6 to the latest 19C. This course is for everybody who likes to make career in database programming, front end programming, ERP, or in general succeed as an IT professional, management people and undergraduate students of any stream. This course is covered on Oracle's LiveSQL platform available on web hence does not require any local installation of Oracle, yet the students can practice on latest version, the current is Oracle 19C. Being on web, students can learn, take notes or do practice sitting anywhere as Oracle LiveSQL is accessible on all the devices - PC, Laptops or even Mobiles. Who this course is for: Students interested in database back end programming Programmers in any other front end language like Java or PHP or Python etc, must learn SQL Engineering students, Computer Science students, Science / Commerce students - All pursuing UG or PG or completed with degree Management people who are required to draw ad-hoc data as per requirement Less
Expired
86 used

[100% OFF] Python Ethical Hacking : Build tools for ethical hacking Free

Python is one of the most used programming languag... Moree in the world and its significance can't be ignored. Python has gained immense popularity recently owing to its performance in various fields like machine learning, data science, data analytics and cyber security. This course is designed in python to make ethical hacking easier for students since python is one of the most easy programming languages to learn. The concepts used in this course are fairly simple and anyone with some knowledge of computer science can try this course. In this course we will learn following topics: Introduction to basics of computer networks What is hacking How to stay anonymous Learn how to track IP location Create your own undetectable malware Execute system commands on the victim machine using backdoor Download and upload files to victim machine How to create a Trojan How to steal wifi passwords stored on the PC How to intercept, manipulate and craft network packets How to perform man in the middle attack Crack password protected zipped files Build your own undetectable key logger Create a botnet with a command and control center How to protect yourself online Less
Expired
180 used

[100% OFF] ML for Business Managers: Build Regression model in R Studio Free

You're looking for a complete Linear Regression co... Moreurse that teaches you everything you need to create a Linear Regression model in R, right? You've found the right Linear Regression course! After completing this course you will be able to: · Identify the business problem which can be solved using linear regression technique of Machine Learning. · Create a linear regression model in R and analyze its result. · Confidently practice, discuss and understand Machine Learning concepts A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course. How this course will help you? If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular technique of machine learning, which is Linear Regression Why should you choose this course? This course covers all the steps that one should take while solving a business problem through linear regression. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. Below are the course contents of this course on Linear Regression: · Section 1 - Basics of Statistics This section is divided into five different lectures starting from types of data then types of statistics then graphical representations to describe the data and then a lecture on measures of center like mean median and mode and lastly measures of dispersion like range and standard deviation · Section 2 - R basic This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R. · Section 3 - Introduction to Machine Learning In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model. · Section 4 - Data Preprocessing In this section you will learn what actions you need to take a step by step to get the data and then prepare it for the analysis these steps are very important. We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bi-variate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation and correlation. · Section 5 - Regression Model This section starts with simple linear regression and then covers multiple linear regression. We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures. We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results, what are other variations to the ordinary least squared method and how do we finally interpret the result to find out the answer to a business problem. By the end of this course, your confidence in creating a regression model in R will soar. You'll have a thorough understanding of how to use regression modelling to create predictive models and solve business problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What is the Linear regression technique of Machine learning? Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value. Linear regression is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y). More specifically, that y can be calculated from a linear combination of the input variables (x). When there is a single input variable (x), the method is referred to as simple linear regression. When there are multiple input variables, the method is known as multiple linear regression. Why learn Linear regression technique of Machine learning? There are four reasons to learn Linear regression technique of Machine learning: 1. Linear Regression is the most popular machine learning technique 2. Linear Regression has fairly good prediction accuracy 3. Linear Regression is simple to implement and easy to interpret 4. It gives you a firm base to start learning other advanced techniques of Machine Learning How much time does it take to learn Linear regression technique of machine learning? Linear Regression is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn Linear regression starts from the basics and takes you to advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to remember whatever you have learnt. Therefore, we have also provided you with another data set to work on as a separate project of Linear regression. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 4 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the R environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in R Understanding of Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture in R where we actually run each query with you. Why use R for data Machine Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Anyone curious to master Linear Regression from beginner to advanced in short span of time Less
Expired
47 used

[100% OFF] Complete Python Bootcamp for Data Science& Machine Learning Free

This comprehensive course will be your guide to le... Morearning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! Enroll in the course and become a data scientist today! Less
Expired
66 used