What are the different models in Machine Learning?

What is a machine learning model?

A machine learning model can be a mathematical representation of a real-world process. The learning algorithm finds patterns in the training data such that the input parameters correspond to the target. The output of the training process is a machine learning model which you can then use to make predictions.

What is the difference between a model and an algorithm?

Algorithms are methods or procedures taken in other to get a task done or solve a problem, while Models are well-defined computations formed as a result of an algorithm that takes some value, or set of values, as input and produces some value, or set of values as output.

What are different models in Machine Learning?

Decision Tree based methods
Linear regression based methods
Neural Network
Bayesian Network
Support Vector Machine
Nearest Neighbor.

Decision Tree based methods

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A decision tree or a classification tree is a tree in which each internal (non-leaf) node is labeled with an input feature.Decision tree learning is a method commonly used in data mining. The goal is to create a model that predicts the value of a target variable based on several input variables.

Linear regression based methods

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Linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression.

Neural Network

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A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature.

Bayesian network

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Bayesian networks are a type of probabilistic graphical model that uses Bayesian inference for probability computations. Bayesian networks aim to model conditional dependence, and therefore causation, by representing conditional dependence by edges in a directed graph

Support Vector Machine (SVM)

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A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples

Nearest neighbor search (NNS)

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Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.

Model selection is the process of choosing between different machine learning approaches – e.g. SVM, logistic regression, etc – or choosing between different hyper parameters or sets of features for the same machine learning approach – e.g. deciding between the polynomial degrees/complexities for linear regression.

What are Machine Learning algorithms and its different types

Machine learning algorithms are programs (math and logic) that adjust themselves to perform better as they are exposed to more data. The “learning” part of machine learning means that those programs change how they process data over time, much as humans change how they process data by learning.

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

The main categories of Machine Learning algorithms are:

Supervised Learning
Unsupervised Learning
Semi-supervised Learning
Reinforcement Learning.

Supervised Learning

Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. It infers a function from labeled training data consisting of a set of training examples.

In this type, human experts act as a teacher where they feed the training data to the computer containing the input/predictors and we show it the right answer and from that data, the computer should be able to learn the patterns.

Some of the commonly supervised algorithms are:

Linear Regression
Logistical Regression
Support Vector Machines
- Learn Machine Learning Adv: Support Vector Machines (SVM) Python
- Learn Machine Learning Adv: Support Vector Machines (SVM) In R
Decision Trees.

2. Unsupervised Learning

Unsupervised learning is a type of self-organized Hebbian learning that helps find previously unknown patterns in data set without pre-existing labels. It is also known as self-organization and allows modeling probability densities of given inputs.

Some of the commonly used unsupervised algorithms are:

K-means clustering
t-SNE
PCA.

3. Semi–supervised learning

Semi-supervised learning is a class of machine learning tasks and techniques that also make use of unlabeled data for training – typically a small amount of labeled data with a large amount of unlabeled data.

4. Reinforcement learning

Reinforcement learning, in the context of artificial intelligence, is a type of dynamic programming that trains algorithms using a system of reward and punishment. A reinforcement learning algorithm, or agent, learns by interacting with its environment.It allows software agents and machines to automatically determine the ideal behavior within a specific context, to maximize its performance.

Some of the commonly used reinforcement learning are:

Q-Learning
Temporal Difference
Monte-Carlo Tree Search.

However, machine learning remains a relatively ‘hard’ problem. There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity, experimentation and tenacity. The difficulty is that machine learning is a fundamentally hard debugging problem.

Top ten Online Courses For Machine Learning [2020]

Looking at all the improvement taking vicinity in machine learning technology, here presenting a listing of on-line guides on Machine Learning that I believe can be of incredible assist for the people who are aspiring to study and master Machine Learning technology. These complete publications have been designed thinking about all the enterprise requirements and help the students to successfully replace their skills and continue to be ahead in the competition. Let us now discuss about those courses

10 best online courses for Machine Learning [2020].

1. Machine Learning And Training Neural Network In MATLAB

Machine Learning is the up and upcoming branch of Artificial Intelligence and it holds great promises for the generations to come. In this course, we will talk about Machine Learning and Artificial Neural Networks and how you can implement a simple Machine Learning Model in MATLAB.

Who this course is for:

Anyone who is interested in learning basic concepts of Machine Learning and Neural networks

What will you learn:

You will learn about Machine Learning and how you can train a simple Model in MATLAB on a simple Dataset. You will get to know some basics of MATLAB too and how you can write and run scripts in MATLAB. You will be able to import your own dataset and train it using different parameters to make some interactive prediction model

Course features:

Duration of the course: 01 hour, 30 Minutes
Number of Lectures: 6
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

2. Road Map To Artificial Intelligence And Machine Learning

This course is created for all the Artificial Intelligence Aspirants who have many queries in mind like

What are prerequisites for learning AI?
What is Road map to start Machine learning project(ML)
How to choose the best programming language for AI ?
How much Mathematical knowledge needed for AI ?
Which is the best AI Engine/Tool/Framework for AI ? and so on..

Who this course is for:

Artificial Intelligence Aspirants
Machine Learning Aspirants
Curiosity to know about Artificial Intelligence

What will you learn:

Basic Idea of Artificial Intelligence and Machine Learning
Prerequisites or Road map to start Machine learning project(ML)
How to choose the best programming language for AI ?
How much Mathematical knowledge needed for AI ?
Which is the best AI Engine/Tool/Framework for AI ?
Why do we need to learn Algorithm?
Types of Machine Learning Algorithms with Real time scenario examples

Course features:

Duration of the course: 54 minutes
Number of lectures: 7
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

3. Machine Learning Using Python : Learn Hands-On

The topics we will be covering in this course are: Python libraries for data manipulation and visualization such as numpy, matplotlib and pandas. Linear Algebra, Exploratory Data Analysis, Linear Regression, Various Classification techniques, Clustering, Dimensionality reduction and Artificial Neural Networks.

Who this course is for:

Students who are pursuing bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Economics or any engineering fields. The students should have a little bit of knowledge in coding and undergraduate level mathematics

What will you learn:

Linear Regression, SVR, Decision Tree Regression, Random Forest Regression
Polynomial Regression
Logistic Regression
K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification
Random Forest Classification
Clustering: K-Means, Hierarchical Clustering
Data Visualization in Python with MatPlotLib and Seaborn
Dimensionality Reduction: PCA, PCA sklearn
Supervised Learning & Unsupervised Learning
Support Vector Machine
Curse of Dimensionality
Neural Networks

Course features:

Duration of the course: 07 hours, 07 minutes
Number of Lectures: 48
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

4. DATA SCIENCE With MACHINE LEARNING And DATA ANALYTICS

The most comprehensive Data Science course in the market, covering the complete Data Science life cycle concepts from Data Collection, Data Extraction, Data Cleansing, Data Exploration, Data Transformation, Feature Engineering, Data Integration, Data Mining, building Prediction models, Data Visualization and deploying the solution to the customer. Skills and tools ranging from Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, programming languages like R programming, Python are covered extensively as part of this Data Science training.

Who this course is for:

All graduates are eligible to learn this course

What will you learn:

DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R, PYTHON, WEKA and SQL
This course is designed for any graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using R programming, Python programming, WEKA tool kit and SQL

Course features:

Duration of the course: 72 hours, 23 minutes
Number of lectures: 86
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

5. Machine Learning Adv: Support Vector Machines (SVM) In R

Are you looking for a complete Support Vector Machines course that teaches you everything you need to create Support Vector Machines in R? Then, this is the ideal course for you. This course will teach you some of the advanced techniques of Machine Learning, which are Support Vector Machines. It covers all the steps that one could take while solving a business through Decision tree.

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 SVM technique from Beginner to Advanced in short span of time

What will you learn:

Get a solid understanding of Support Vector Machines
Understand the business scenarios where Support Vector Machines is applicable
Tune a machine learning model’s hyperparameters and evaluate its performance.
Use Support Vector Machines to make predictions

Course features:

Duration of the course: 03 hours, 04 minutes
Number of lectures: 26
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

6. Amazon Alexa 101: Publishing Alexa Skills Without Coding

This is the perfect time to learn Alexa Skill Development. Soon there will be lot of demand for Alexa Skill Developers, as many companies wants to add Alexa voice control to their products and services.This Alexa Skill tutorial teaches required skills to become Alexa Skill Developer without having to code. This course covers almost all features of Alexa Skills with real-world example skills (including a published skill).After completing this course, you should be able to build any Alexa skill.

Who this course is for:

Those who want to learn Alexa Skills Development WITHOUT coding

What will you learn:

Publishing Alexa Skills in Amazon US and other countries
Create your own custom skills for Amazon Echo devices
100% Satisfaction: This course has a 30 days money-back guarantee
Learn how to create a basic conversation between Amazon Alexa and a user
Creating Trivia quizzes
Creating a flash briefing skill
Exporting Sounds from dropbox and audio players
Creating and Storing user input in variables
JSON API integration using google spreadsheets
Using live tweets from twitter and integrating it with Alexa
Getting Real Time User Feedback from AirTable
Monetise from alexa skills and earn profits
After finishing this course, you should gain full mastery of creating and publishing Amazon Alexa Skills without coding
5 Publishing Secrets for Top Alexa Skills And Tips For Getting Featured
Monitoring and Data analysis for your Alexa App

Course features:

Duration of the course: 02 hours, 07 minutes
Number of lectures: 15
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

7. Machine Learning Using R And Python

Through this course, you will learn to solve data-driven problems and implement your solutions using the powerful yet simple programming language like R and Python and its packages. After completing this course, you will gain a broad picture of the machine learning environment and the best practices for machine learning techniques

Who this course is for:

All graduates or pursuing students.This course has been prepared for professionals aspiring to learn the basics of R and Python and develop applications involving machine learning techniques such as recommendation, classification, regression and clustering.

What will you learn:

This course has been prepared for professionals aspiring to learn the basics of R and Python to develop applications involving machine learning techniques such as recommendation, classification, and clustering. Through this course, you will learn to solve data-driven problems and implement your solutions using the powerful yet simple programming language R and Python with its packages. After completing this course, you will gain a broad picture of the machine learning environment and the best practices for machine learning techniques.

Course features:

Duration of the course: 69 hours, 42 minutes
Number of lectures: 83
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

8. Machine Learning And Data Science Using Python For Beginners

Artificial Intelligence, Machine Learning, and Deep Learning are among the most discussed terms of the present IT industry. This course focuses on teaching mainly Machine Learning and Data Science concepts to beginners using Python programming language with libraries such as Scikit-learn, SciPy, Matplotlib & Pandas.

Who is this course for:

Anyone who wants to learn Machine Learning and Data Science using Python programming language can opt for this course. This course is of great use to beginners who want to learn these technologies.

What will you learn:

Machine Learning and Data Science for programming beginners using python with scikit-learn, SciPy, Matplotlib & Pandas.

Course features:

Duration of the course: 10 hours, 19 minutes
Number of lectures: 90
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

9.Learn Artificial Intelligence For Beginners

In this course you learn about the fundamentals concepts of the field of Artificial Intelligence. This course is designed specifically for beginners where we will take you step by step through our intuitive curriculum. Please have a look through the concepts and work your way through the quizzes.

Who this course is for:

Anyone who is a beginner at AI
Anyone who wants to learn about Artificial Intelligence
Anyone who wants to start a business with Artificial Intelligence
Anyone who wants to know about the AI industry
Students, Scientist, Engineers

What will you learn:

Definition of Artificial Intelligence
Application of Artificial Intelligence
History of Artificial Intelligence
Definition of Machine Learning
Types of Machine Learning
Industry Situation and Opportunities
What are Expert Systems?
What is Computer Vision?
What is Fuzzy Logic System?

Course features:

Duration of the course: 01 hour, 08 minutes
Number of lectures: 21
Language: English.
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sing up for this course here

10. Practical Deep Learning: Image Search Engine

Artificial intelligence is one of the fastest growing fields of computer science today and the demand for excellent AI Engineers is increasing day in and day out. This course will help you stay competitive in the AI job market by teaching you how to create a Deep Learning End-to-End product on your own.

Who is this course for?

As you can see the course is meant to teach you how to create your own Deep Learning product from scratch.

What will you learn:

What are Image-to-Image Search engines
How to build your AI based Image-to-Image Search engine
How to create simple web based interface for your Deep learning models using the Python framework Flask
Coding a Convolutional Neural Network (CNN) from scratch in Tensorflow 1.10.0
Using the Python framework Flask to serve a Deep Learning model in production
How to create an End-to-End pipeline for any Deep Learning model using Tensorflow
How to create a Flask application from scratch

Course features:

Duration of the course: 01 hour, 33 minutes
Number of lectures: 25
Language: English
Course type: Self-paced, online
Access on Android and iOS App: Yes.

You can sign up for this course here

I believe that here I have given the best collection of online courses on Machine Learning to my readers. The primary purpose of this blog is to help people find all the best courses on Machine Learning under one umbrella. I hope this blog has been successful in achieving its goal.

Best Beginners Online Courses On Robotics and Artificial Intelligence

Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. Robotics is a branch of engineering that involves the conception, design, manufacture, and operation of robots. This field overlaps with electronics, computer science, artificial intelligence, mechatronics, nanotechnology and bio engineering. Robotics involves building robots whereas AI involves programming intelligence.

The ultimate goal of artificial intelligence is to create computer programs that can solve problems and achieve goals like humans would. According to data from the Robotic Industry Association, the market for industrial robots continues to rise.So both artificial intelligence and robotics will create the majority of the employment sector in the coming ages. Following are some of the best beginners tutorials for robotics and artificial intelligence which may help you to start your career with.

Learn Robotics Fundamentals

Robotics In-Depth

Introduction To Robotics & Entrepreneur

Artificial Intelligence For Beginners

The Basic Fundamentals Of Artificial Intelligence

Artificial Intelligence In FinTech

Artificial Intelligence In Digital Marketing In 2020

Learn Robotics Fundamentals You Need To Know

Those who are interested in Robotics would get a chance to know the basics of Robotics. For beginners, it is very adaptive without any prior knowledge of Robotics. It covers the Fundamental Theory of Robotics, Introduction to Motors (Servo, DC and Stepper) and Bluetooth. The product that you will learn to make at the end of this course is a Robotic Car.

What will you learn:

For beginners, it is very adaptive without any prior knowledge of Robotics
The product that you will learn to make at the end of this course is a Robotic Car
You will be able to easily move on to the advanced Robotics courses
Learn to program robots in a professional way
Build distributed software and drivers for a robot

Duration : 01:22:05

Rating: 4.5 out of 5

You can sign up here

Robotics In-Depth Course

Robotics is heavily mystified in today’s public awareness. People are simply not aware of what machines can and can’t do. Robotics helps in addressing the growing demand for teaching Science, Technology, Engineering, and Math in schools. It is the course that describes the design, construction, operation, and ultimately the use of Robots. By making Robots, students can create their own devices and gadgets that interact with the real world. This is a profound and empowering experience, which greatly impacts a student’s life. Teaching Robotics to young students throughout their learning can increase their ability to be Creative and Innovative thinkers and more productive members of society.

What will you learn:

This course is designed to help you make a programmed Robot
Our primary focus is to grow the programming and electronics skills of the students with the help of the Robotics In-Depth Module course
We help you to understand the Robotics
Associated components which ultimately improve your Logical & Analytical skills.

Duration : 01:54:58

Rating: 4.2 out of 5

You can sign up here

Introduction To Robotics & Entrepreneur

This course is going to give anyone who is interested in Robotics a Chance to learn the basics without any prior experience. The course contains content which is suited for Beginners. This course will also allow anyone to learn Entrepreneurship through your product. You would learn how to make your Robots and create a company out of it by going through,

Fundamental Theory of Robotics
Introduction to Sensors & Actuators
Learn and manipulate Motor Drives
Brief about Entrepreneurship
Brief about Market Research
Brief about Product Developmet

What will you learn:

You will be able to build simple robots
You will be able to understand how businesses work
You will be able to create a product
You will learn Product development
You will learn to control simple motors
You will be able to market your product
You will be able to go to advanced technical courses after this course.

Duration : 04:09:27

Rating: 4.3 out of 5

You can sign up here

Learn Artificial Intelligence For Beginners

Here in this course you will learn the following topics;

Definition of Artificial Intelligence
Application of Artificial Intelligence
History of Artificial Intelligence
Definition of Machine Learning
Types of Machine Learning
Industry Situation and Opportunities
What are Expert Systems?
What is Computer Vision?
What is Fuzzy Logic System?

Duration : 01:08:46

Rating: 4.3 out of 5

You can sign up here

Learn The Basic Fundamentals Of Artificial Intelligence (AI) In Software Testing

This course is designed for both testers and developers. This course is also great for anyone who want to learn what is Artificial Intelligence and how it is used in Software Testing.This course will teach you how AI-assisted test automation can transform the UI. This course will also teach you Artificial Intelligence (AI) and it’s relationship with Machine Learning and Deep Learning.

What will you learn:

You will learn what is Artificial Intelligence (AI) and what is the relationship of AI with Machine Learning and Deep Learning
You will also learn how AI test automation tool uses machine learning to speed-up the authoring, execution and maintenance of automated tests
Tester who want to develop their testing skills in the test automation with Artificial Intelligence (AI) and Developer who want to execute their unit test in automated way using Artificial Intelligence (AI)

Duration : 00:38:41

Rating: 4.1 out of 5

You can sign up here

Artificial Intelligence In FinTech

This course is recommended for anyone who is interested in learning about application of AI and ML in the financial services industry. At the end of this course, you will be familiar with basic concepts of ML and AI and appreciate how they are being used in the Financial Services industry.

What will you learn:

Basic concepts related to Data Science, Machine Learning and Artificial Intelligence
History of Machine Learning and AI in Financial Services and FinTech
Closer look at several ML and AI financial services use cases (B2B and B2C)
Future trends and its potential impact to the financial services industry – including job displacement and new career options.

Duration : 01:36:23

Rating: 4.4 out of 5

You can sign up here

Artificial Intelligence In Digital Marketing In 2020

Being smart in business means knowing what’s just around the corner. It means thinking ahead and preparing for inevitable changes that will impact the way business is conducted.This is what allows a business to be resilient and to thrive in a changing environment.

What will you learn:

What Is AI And Machine Learning?
Google As An AI-First Company
Preparing For Semantic Search
Big Data
Computer Version
Advertising
Email Marketing
Chatbots
Developing Your AI Skills – Using SQL
How To Future Proof Your Marketing

Duration :00:48:12

Rating: 4.6 out of 5

You can sign up here

According to the Bureau of Labor Statistics, demand for qualified robotics engineers and artificial intelligent experts are expected to grow by as much as 13 percent through 2020. So make use of the given opportunity and get in to a dignified career where all your dreams are met.

The Best Aerospace Engineering – Basic information, courses, careers and scope

Aeronautical Engineering is a generic branch of engineering that attracts students with pastime in airplanes and their mechanism. The principal job of an Aeronautical Engineer is to devise plane and propulsion systems, but with time, the engineer is given many more obligations to lift out.Recruitment possibilities are handy in protection offerings and aviation industry.

Aerospace engineers typically specialize in one of two types of engineering: aeronautical or astronautical. Aeronautical engineers work with aircraft. They are involved primarily in designing aircraft and propulsion systems and in studying the aerodynamic performance of aircraft and construction materials.

Astronautical engineering is a very unique field that allows individuals to engage in tasks that some can only dream about. This type of engineering is also known as rocket science and can seem almost unrealistic as those who work in the field actually create products such as rocket ships.

Entry requirements:

You’ll want to be tremendously equipped in arithmetic and physics in order to practice –count on your competency in these two subjects to be carefully tested. And, if your diploma is taught in English and you are a global student, you may additionally need to prove your skill ability through a standardized examination such as the IELTS or take an English language direction prior to moving forward your degree in order to obtain a pupil visa or entry into the program.

Future Growth Prospects:

Studying aerospace engineering gives a range of career options. Potential fields to specialise in comprise thermodynamics, propulsion, aerodynamics, and celestial mechanics. If every person has a ardour for a precise aerospace product, for instance, rockets, missiles, helicopters, or military jets he/she might also choose to specialise in that unique product as well.

As per a latest report, it has been mentioned that employment of aerospace engineers is predicted to grow with the aid of 10% from 2020 to 2026. Aircrafts are being redesigned to motive a smaller quantity of noise air pollution and have better gasoline efficiency, which will demand for greater lookup and development. Aeronautical Engineers are in demand nationally and internationally. They are required in non-public and public Airline Services as properly as aircraft-manufacturing units. At the start, these engineers are hired as graduate engineer trainees or Junior Engineers. Countries like the US, UK, France, and Germany rent Aeronautical Engineers. In NASA, a accurate variety of Indian Aeronautical engineers can additionally be found.

Job Profile

Aeronautical Engineers as the name suggest, specialize in creation and maintenance of aircraft and aircraft related technologies for improved functioning of aviation and defense industry.

Some of the aeronautical engineering jobs are:

Aeronautical Engineers:

Aeronautical Engineers are trained to design aircrafts.

Aeronautical Mechanical Engineers:

Aeronautical Mechanical Engineer are responsible for the upkeep and maintenance of aircraft engines.

Aeronautical Electronic Engineers:

Aeronautical electronic engineers are hired for maintenance of electrical and electronic equipment used for navigation, radar and radio communication, etc.

Flight Engineers:

Flight engineers are the ones who are responsible for smooth performance of the aircraft during the flight.

How to start with:

Introduction To Aeronautical Engineering

is a course you will learn and enhance all the fundamentals require for Aerospace Engineering.

Basic knowledge:

High School Physics
Basic Math

What will you learn:

How Aircraft’s Fly
Calculation of forces acting on Aircraft
Cockpit View & its Nomenclature
Different Flight Structures
Flight Stability

Learn More:

The Best Robotic Introductory Course online

Robotics is a scientific and engineering discipline that is focused on the understanding and use of artificial, embodied capabilities.It deals with the design, construction, operation, and use of robots, as well as computer systems for their control, sensory feedback, and information processing.Most robots today are used to do repetitive actions or jobs considered too dangerous for humans. Robots are also used in factories to build things like cars, candy bars, and electronics.

The scope of opportunities with Robotic Engineering is on the rise world wide. Let’s take a look at the subject and its scope. Robotics Engineering is about designing, structuring, building and application of robots using the computer for their processing and manipulation.

Areas to learn in Robotics:

Robotic engineering.
Motion planning.
Artificial intelligence.
Machine learning.
Computer vision.
Computer programming for robotics.

Best College Majors For Robotics:

Electrical/Electronic Engineering.
Mechanical Engineering.
Computer Science.
Mathematics.
Design and Technology.
Computing and Programming.

The Top Robotic Introductory Course online

Fundamental Theory of Robotics
Introduction to Sensors & Actuators
Learn and manipulate Motor Drives
Brief about Entrepreneurship
Brief about Market Research
Brief about Product Development

The course is uniquely designed with a blend of Business theory with the technical theory of Robotics Engineering suitable for any Budding Entrepreneur who wants to know the ins and outs of the field.

Who this course is for:

Anyone who wants to learn Robotics
Anyone who wants to study Robotics & Engineering
Anyone who want to learn Entrepreneurship
Anyone who wants to create a Company
Anyone who wants to learn Product Development
Anyone who wants to learn Marketing strategies

Basic knowledge needed:

You should have little experience with Electronics
You should have passion for Making
You should have an interest for Engineering
You should know little bit of Programming

What will you learn:

You will be able to build simple robots
You will be able to understand how businesses work
You will be able to create a product
You will learn Product development
You will learn to control simple motors
You will be able to market your product
You will be able to go to advanced technical courses after this course.

Robotics is a hobby that, as you program and build your own robots, can bring lasting enjoyment and even become a future career. If you want to learn robotics, the best way to do so is developing proficiency in computer science, coding, physics, and linear algebra.The future world is in the hands of robots.Give it a try.

The best Online Tutorials On Artificial Intelligence For Beginners

The ultimate goal of artificial intelligence is to create computer programs that can solve problems and achieve goals like humans would. There is scope in developing machines in robotics, computer vision, language detection machine, game playing, expert systems, speech recognition machine and much more.

To take your first steps down the artificial intelligence career path, hiring managers will likely require that you hold at least a bachelor’s degree in mathematics and basic computer technology. However, for the most part, bachelor’s degrees will only get you into entry-level positions.Following are some of the online tutorials for those who wish to start their career in artificial intelligence.

6 Best Artificial Intelligence (AI) Certification Courses,Tutorials Online

1. Learn The Basic Fundamentals Of Artificial Intelligence (AI) In Software Testing

After you have completed this course you should be able to teach your friends or coworkers the importance of Artificial Intelligence in Software Testing. You should be able to host the lunch and learn session for your friends or coworkers. By looking at Test Automation Demo included in this course, you should able to build test automation project for your company’s web applications.

What will you learn:

You will learn what is Artificial Intelligence (AI) and what is the relationship of AI with Machine Learning and Deep Learning
You will also learn how AI test automation tool uses machine learning to speed-up the authoring, execution and maintenance of automated tests
Tester who want to develop their testing skills in the test automation with Artificial Intelligence (AI) and Developer who want to execute their unit test in automated way using Artificial Intelligence (AI)

Duration : 00:38:41

Rating: 4.5 out of 5

You can Sing up here

2. Let WIX, Artificial Intelligence (ADI) Build Your Website

This course will give you a good introduction to WIX Artificial Intelligence (ADI) which will create your web site with features such as Online Shopping, Online booking, Blog and more…Think of ADI as your new Web Site Robot Builder & an intuitive learning tool which does things for you and teaches you how things are done.

By the end of this course you will be able to:

Use WIX ADI to let it create your own web site in minutes
Let it change the web design, themes, color, fonts, add animation etc. to suite your need and obtain the desired look & feel
You will be able use WIX ADI tool to create your desired web site whether it is an Online Shop, Online booking, Blog, business or consulting services depends on how you instruct ADI
You will master the tool and it will improve your site to give it a professional look and feel

Duration : 00:17:53

Rating: 4.2 out of 5

You can Sign up here

3. Learn Artificial Intelligence For Beginners

This course will give you the knowledge of the fundamentals concepts of the field of Artificial Intelligence. This course is designed specifically for beginners where we will take you step by step through our intuitive curriculum. Please have a look through the concepts and work your way through the quizzes.

If anyone already has the knowledge of the fundamentals, please check through the curriculum to see if you need this course, after all our time is precious. We do not want you to repeat anything. We would highly encourage you to look at the contents menu first and see if you really need to take this course.

Who this course is for:

Anyone who is a beginner at AI
Anyone who wants to learn about Artificial Intelligence
Anyone who wants to start a business with Artificial Intelligence
Anyone who wants to know about the AI industry
Students, Scientist, Engineers

What will you learn

Definition of Artificial Intelligence
Application of Artificial Intelligence
History of Artificial Intelligence
Definition of Machine Learning
Types of Machine Learning
Industry Situation and Opportunities
What are Expert Systems?
What is Computer Vision?
What is Fuzzy Logic System?

Duration : 01:08:46

Rating: 4.4 out of 5

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4. Road Map To Artificial Intelligence And Machine Learning

This course is created for all the Artificial Intelligence Aspirants and will discuss the following

What are prerequisites for learning AI?
What is Road map to start Machine learning project(ML)
How to choose the best programming language for AI ?
How much Mathematical knowledge needed for AI ?
Which is the best AI Engine/Tool/Framework for AI ? and so on…

Who this course is for:

Artificial Intelligence Aspirants
Machine Learning Aspirants
Curiosity to know about Artificial Intelligence

Basic knowledge

Passion to learn alone is enough to start this course

What will you learn

Basic Idea of Artificial Intelligence and Machine Learning
Prerequisites or Road map to start Machine learning project(ML)
How to choose the best programming language for AI ?
How much Mathematical knowledge needed for AI ?
Which is the best AI Engine/Tool/Framework for AI ?
Why do we need to learn Algorithm?
Types of Machine Learning Algorithms with Real time scenario examples

Duration : 00:54:03

Rating: 4.1 out of 5

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5. Artificial Intelligence In FinTech

In recent years, explosion of data, inexpensive computing power and developments in big data processing infrastructure have led to increased use of Machine Learning in all industries. So, financial services incumbents as well as FinTech startups are using Machine Learning and Data Science to improve business economics and maintain/create their competitive advantage. Since data volume is only expected to increase in this digital world, Machine Learning and Artificial Intelligence are expected to get ubiquitous in the coming years with wide range of implications for FinServ and FinTech companies.This course is recommended for anyone who is interested in learning about application of AI and ML in the financial services industry.

This course will cover:

Basic concepts related to Data Science, Machine Learning and Artificial Intelligence
History of Machine Learning and AI in Financial Services and FinTech
Closer look at several ML and AI financial services use cases (B2B and B2C)
Future trends and its potential impact to the financial services industry – including job displacement and new career options.

Duration : 01:36:23

Rating: 4.3 out of 5

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6. Artificial Intelligence In Digital Marketing In 2020

This video course will help you to prepare, and explain a number of concepts like AI vs Machine Learning,How to conduct SEO now that Google is an “AI first” company,Chat bots,Programmatic advertising,Big data,Rank Brain,Digital assistants,Data science,SQL,Latent Semantic Indexing and The future of internet marketing.In this course, you will gain a crystal ball with which to gaze into the future of internet marketing, and to ensure that you are ready for all those changes when they come.

What will you learn

What Is AI And Machine Learning?
Google As An AI-First Company
Preparing For Semantic Search
Big Data
Computer Version
Advertising
Email Marketing
Chatbots
Developing Your AI Skills – Using SQL
How To Future Proof Your Marketing

Duration :00:48:12

Rating: 4.2 out of 5

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