double quote Supercharge your career growth in Artificial Intelligence

Artificial Intelligence Projects

4.49
learner icon
34.9K+ Learners
beginner
Beginner

Take a free artificial intelligence projects course & get hands-on experience to handle ai problems.

What you learn in Artificial Intelligence Projects ?

tick
ANN Model
tick
Keras
tick
Python
tick
Weights
tick
Biasis
tick
Activation

About this Free Certificate Course

Artificial intelligence is one of the most common topics and the most trending domain today. The Artificial Neural Network (ANN) is a data-processing paradigm inspired by the brain. It learns by doing, just like people. An ANN is designed for a given purpose, such as pattern recognition or data classification, through a learning process. This course will also predict stock prices using Deep learning techniques. The model training approach is discussed in a case study. The course is structured in a way that helps you to implement the solution and models of Artificial Intelligence to the problems. To do well in the real world and learn business applications of AI, the best practice is learning through artificial intelligence projects. 

Explore India's best artificial intelligence course to gain skills and succeed in the global environment. The 12-month online course provides personalised mentorship with career support and access to our vast professional network.

 

Course Outline

Image Processing using Python
What is Image Processing?
Human brain vs Neural Network
How image input works in computer?
What is CNN?
Layers in CNN
Face Recognition using Python
Getting started with OpenCV Demo Creating a Virtual Assistant using Python
What is Chatbot?
Building a Virtual Assistant using Python
Architecture of ANN
Loss Functions in Neural Networks
Back Propagation in Neural Networks
Gradient Descent
Keras Basic ANN Architecture - Demo
Dataset Overview and Model Framework
ANN Application Credit Data - Demo
What is Dead Neuron Problem?
Is Scaling necessary?
What is Time Series Forecasting?
Basics of Steps in Forecasting
ANN and RNN
Model Training

What our learners say about the course

Find out how our platform helped our learners to upskill in their career.

4.49
Course Rating
70%
21%
5%
1%
3%

Artificial Intelligence Projects

With this course, you get

clock icon

Free lifetime access

Learn anytime, anywhere

medal icon

Completion Certificate

Stand out to your professional network

medal icon

4.5 Hours

of self-paced video lectures

share icon

Share with friends

Frequently Asked Questions

Why do Artificial Intelligence Projects Fail?

There can be multiple reasons for AI / ML projects failure. Some are :

  • Insufficient Data

  • Lack of skilled Data Scientists

  • Lack of Data Strategy

  • Training Data problem

  • Deficient Budget 

  • Too complex project

  • Lack of leadership support

  • Unexpected complications

 

What makes a good Artificial Intelligence project?

To make a good AI project, you can follow below steps :

  • You need to determine the purpose

  • Determine the objective of the project

  • Do your data building part wisely

  • Check and measure the outcome of the project

  • Make use of the visualization tool

What are some cool AI projects?

Some of the cool Artificial Intelligence projects can be :

  • Voice-based Virtual Assistant

  • Facial Emotion Recognition and Detection

  • Handwritten Digits Recognition

  • Next Word Predictor

  • T-rex Dino Bot

  • Chatbot

  • Self-Driving Car

  • Online Assignment Plagiarism Checker

  • Stock Price Prediction

What are AI projects around us?

There are several AI projects that are around us, and we use them frequently. Some of the best AI projects are listed below :

  • Alexa

  • Microsoft Cortana

  • AlphaGo

  • IBM Watson

  • Google Brain

  • Self-driving car

  • Manufacturing robots

  • Smart Assistants

10 Million+ learners

Success stories

Can Great Learning Academy courses help your career? Our learners tell us how.

And thousands more such success stories..

Related Artificial Intelligence Courses

50% Average salary hike
Explore degree and certificate programs from world-class universities that take your career forward.
Personalized Recommendations
checkmark icon
Placement assistance
checkmark icon
Personalized mentorship
checkmark icon
Detailed curriculum
checkmark icon
Learn from world-class faculties

Other Artificial Intelligence tutorials for you

 

Artificial Intelligence Projects

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is one of the most trending topics in today’s world. AI is an ability of a machine to learn and think. AI helps machines to work on their own rather than giving commands explicitly. The specific application of artificial intelligence includes Natural language processing (NLP), machine vision, expert system, and speech recognition. To build a strong foundation and cover basic concepts, you can enroll in an introduction to artificial intelligence course for free. 

 

The artificial intelligence programming core part is three cognitive skills :

  1. Learning

  2. Reasoning

  3. Self-correction

 

1. Learning Process: The learning process focuses on collecting data and creating algorithms that can convert data into meaningful information. These algorithms help to give stepwise instruction to perform a specific task.

 

2. Reasoning Process: The reasoning process mainly focuses on choosing the right algorithm to reach the desired output.

 

3. Self-correction Process: This AI programming is designed to improve algorithms so that they provide more accurate results continuously.

 

Type of Artificial Intelligence    

 

1. Reactive Machine: These AI systems don’t have memory, so they can’t use it to past experiences to predict future ones continuously. Also, they are tasks specific. They can be used for simple classification and patterns recognition tasks.  For example- Deep Blue, an IBM chess program.

 

2. Limited Memory: These AI systems have a memory, so they use the historical data to predict future ones. They can be used for complex classification.For example- Self-driving cars.

 

3. Theory of Mind: These AI systems have the social intelligence to under emotions. These types of systems are used to predict human behavior. This can deliver the personal experience to everyone based on their motives and needs. These kinds of AI are work-in-progress. For example- Autonomous Car

 

4. Self-awareness: These AI systems are self-aware and know their internal states. These systems don’t exist.

 

 

Applications of Artificial Intelligence

 

1. AI in Banking: The banking industry is successfully deploying chatbots to help their customers in transactions and tell them about services and offerings without any human intervention. They are also using AI-based applications to improve decision-making processes for loan approval, fraud detection, investment opportunity identification, etc.

 

2. AI in Business: Companies are using machine learning algorithms for customer relationship management (CRM) in the business industry. They are also using Chatbots that are incorporated into their websites to help customers immediately without any human interaction. 

 

3. AI in Finance: The finance industry uses AI applications for fraud detection and provides financial advice. IBM Watson is used to buying home. AI application also helps in investment in the financial field.

 

4. AI in Healthcare: The healthcare industry uses machine learning algorithms for diagnoses purpose, which is giving better results than humans. One of the best examples is IBM Watson, which can understand natural language and reply to the question as well. The other applications, such as Chatbots, virtual health assistants, etc., are used to give medical advice, schedule appointments, and perform many other administrative tasks.

 

5. AI in Transportation: The autonomous car is an example of an AI application in the transportation field. AI technologies are also used for traffic prediction, predicting flight delays, etc. AI-powered chatbots are used to answer queries for faster responses.   

 

6. AI in Data Security: With the rapid increase in data, cyber-attacks are also increasing in the digital world. Artificial Intelligence helps to make data secure and safe from cyber-attacks. For example, AEG bot and AI2 platforms are useful for determining software bugs and cyber attacks. 

 

7. AI in Entertainment: The use of AI-based applications are used for entertainment purposes such as Amazon or Netflix. With the help of Machine Learning and Artificial Intelligence algorithms, they show the recommendations for shows and programs. You can also enrol for basics of machine learning course here.

 

 

Artificial Intelligence Projects

 

  1. Artificial Intelligence Projects for Beginners

  • Stock Price Prediction

  • Handwritten Digits Recognition

  • Lane Line Detection

  • Chatbots

  • Predicting Housing Price

  • Spam Classifier

  • Optimal Path

  • Smart AI Chatbot

 

  1. Artificial Intelligence Projects for Intermediate 

  • Game of Chess

  • Pneumonia Detection

  • Customer Recommendation

  • Next Word Predictor

  • Website Evaluation

  • Fire Detection and Localization

  • Home Automation System

  • Attendance System Using Face Detection

  • Advertising and Product Suggestion

 

  1. Artificial Intelligence Projects for Advance

  • Facial Emotion Recognition

  • Voice-based Virtual Assistance

  • Fake Product Review Monitoring System

  • Price Negotiator Chatbot

  • Personality Prediction System

  • Heart Disease Prediction

  • Music Recommendation App

  • Self-Driving Car

  • Learn to Drive with Reinforcement Learning

 

 

Advantages and Disadvantages of Artificial Intelligence

 

Advantages

 

  1. AI-based applications are available 24x7 that help people to connect anytime from anywhere.

  2. The AI applications can do repetitive tasks again and again, which can be boring tasks for human beings.

  3. Artificial intelligence helps to make decisions faster and than a human being.

  4. Daily applications such as Siri, Ok Google, Alexa, Cortana, etc., are helping people with scheduling reminders, finding locations, taking a phone call, replying to email, and many more.

  5. AI-based applications reduce human error, thus making the applications more accurate and useful.

 

Disadvantage

 

  1. Building AI applications requires hardware and software with the latest requirements, and they are very costly. It is difficult to maintain and repair as its expensive.

  2. Artificial intelligence helps machines learn and do tasks independently, making human beings lazier and addicted to these inventions.

  3. The machine can perform tasks independently, but they can get crashed or produce the wrong output in some cases, which can be a major drawback.

  4. When it comes to efficiency, then no doubt, the machine provides better efficiency, but when it comes to bonding and team management, it cannot replace human connection.

  5. AI helps to do repetitive tasks repeatedly and is available 24x7, which is more efficient than human beings, so many companies are replacing humans and bringing AI robots to do the same tasks.

Enrol for Free