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Artificial Intelligence


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Ranked #1 Best Artificial Intelligence Program By Mr. Anil Kumar

Artificial Intelligence (AI) is a field of computer science that creates machines capable of human-like tasks, such as decision-making, pattern recognition, and speech recognition. AI improves efficiency and productivity in various industries and continues to shape our world. Complete the course to get an assured job with an average salary of 6.5 LPA.


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ARTIFICIAL INTELLIGENCE

Category: Machine Learning/Artificial Intelligence

About Artificial Intelligence(AI)

Artificial intelligence (AI) is the ability of machines to perform tasks that would normally require human intelligence, such as learning, problem-solving, and decision-making. AI is achieved through the development of algorithms and systems that can process and analyse data, and make decisions or predictions based on that data.

There are two main types of artificial intelligence: narrow or weak AI, and general or strong AI. Narrow or weak AI is designed to perform a specific task, such as recognizing speech or playing a game. General or strong AI, on the other hand, is designed to be able to perform any intellectual task that a human can.

AI is used in a wide range of applications, including image and speech recognition, natural language processing, predictive modelling, and self-driving cars. It is an active area of research and development, and is expected to continue to have a significant impact in the coming years.

Key Features of Artificial Intelligence

Some key features of artificial intelligence (AI) include:

  1. 1. Ability to learn:  AI systems are able to learn from data and improve their performance over time. This is achieved through the use of machine learning algorithms, which are able to find patterns and relationships in data and use them to make predictions or decisions.

  2. 2. Ability to make decisions:  AI systems are able to analyse data and make decisions based on that data. This can be used to enable autonomous systems, such as self-driving cars, to make decisions based on sensory data.

  3. 3. Ability to process and analyse large amounts of data:  AI systems are able to process and analyse large amounts of data, making them useful for tasks such as image and speech recognition, natural language processing, and predictive modelling.

  4. 4. Ability to adapt:  AI systems are able to adapt to new situations and environments, allowing them to learn and improve over time.

  5. 5. Ability to communicate:  AI systems can be designed to communicate with humans using natural language, making them more accessible and easier to use.

Overall, AI systems are characterized by their ability to learn, make decisions, process and analyze large amounts of data, adapt to new situations, and communicate with humans. These features make AI systems useful for a wide range of applications, including image and speech recognition, natural language processing, predictive modelling, and autonomous systems.

Scope of Artificial Intelligence

Artificial intelligence (AI) is a broad field that encompasses a range of technologies and techniques for creating intelligent machines that can think and act like humans. The scope of AI includes everything from simple rule-based systems to more complex cognitive architectures and machine learning algorithms. Some of the key areas of AI include:

  1. 1. Natural language processing (NLP):  This subfield deals with the interactions between computers and human languages, particularly in the areas of speech recognition, language understanding, and machine translation.

  2. 2. Computer vision:  This subfield is focused on developing algorithms that allow machines to interpret and understand visual information from the world, such as image and video data.

  3. 3. Machine learning:  This subfield focuses on creating algorithms and models that allow machines to learn from data and improve their performance on a specific task over time. Machine learning has been used to develop image recognition systems, natural language processing tools, and even self-driving cars.

  4. 4. Robotics:  This subfield involves creating intelligent machines that can perform tasks autonomously, such as assembling products in a factory or exploring a planet.

  5. 5. Expert systems:  These are computer programs that mimic the decision-making abilities of a human expert in a particular field.

Overall, the scope of AI is vast and encompasses many different technologies and applications, with the ultimate goal of creating intelligent machines that can assist and augment human capabilities.

Applications of Artificial Intelligence

Artificial intelligence (AI) has a wide range of applications, and it is being used in many different industries to automate tasks, improve efficiency, and augment human capabilities. Some examples of the ways in which AI is being used include:

  1. 1. Automation:  AI is being used to automate a wide range of tasks, including customer service, data entry, and scheduling.

  2. 2. Predictive analytics:  AI is being used to analyse data and make predictions about future events, such as customer behaviour or market trends.

  3. 3. Image and speech recognition:  AI is being used to enable computers to recognize and interpret images and speech, which has applications in fields such as security and healthcare.

  4. 4. Natural language processing:  AI is being used to enable computers to understand and generate human language, which has applications in fields such as customer service and language translation.

  5. 5. Robotics:  AI is being used to enable robots to perform tasks, such as assembly line work or home cleaning.

  6. 6. Personal assistants:  AI is being used to enable virtual personal assistants, such as Apple's Siri or Amazon's Alexa, which can help users with tasks such as setting reminders or answering questions.

Overall, AI has many applications and is being used in a wide range of industries to automate tasks, improve efficiency, and augment human capabilities.


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Course Syllabus

    •   PRE PREPARATORY CONTENT
    • INTRODUCTION TO PYTHON FOR DATA ANALYSIS
    • PYTHON FOR DATA SCIENCE
    • MATH FOR MACHINE LEARNING
    • DATA VISUALISATION IN PYTHON
    • DATA ANALYSIS USING SQL
    • ADVANCED SQL
    •   STATISTICS ESSENTIAL
    • ANALYTICS PROBLEM SOLVING
    • INVESTMENT ASSIGNMENT
    • INFERENTIAL STATISTICS
    • HYPOTHESIS TESTING
    • EXPLORATORY DATA ANALYSIS
    • GROUP PROJECT
    •   MACHINE LEARNING – 1
    • LINEAR REGRESSION
    • LINEAR REGRESSION ASSIGNMENT
    • LOGISTIC REGRESSION
    • NAIVE BAYES
    • MODEL SELECTION
    •   MACHINE LEARNING – II
    • ADVANCED REGRESSION
    • SUPPORT VECTOR MACHINE (OPTIONAL)
    • TREE MODELS
    • MODEL SELECTION – PRACTICAL CONSIDERATIONS
    • BOOSTING
    • UNSUPERVISED LEARNING: CLUSTERING
    • UNSUPERVISED LEARNING: PRINCIPAL COMPONENT ANALYSIS
    •   NATURAL LANGUAGE PROCESSING
    • LEXICAL PROCESSING
    • SYNTACTIC PROCESSING
    • SYNTACTIC PROCESSING-ASSIGNMENT
    • SEMANTIC PROCESSING
    • BUILDING CHATBOTS WITH RASA
    •   DEEP LEARNING
    • INTRODUCTION TO NEURAL NETWORKS
    • SYNTACTIC PROCESSING
    • NEURAL NETWORKS – ASSIGNMENT
    • CONVOLUTIONAL NEURAL NETWORKS -INDUSTRY APPLICATIONS
    • RECURRENT NEURAL NETWORKS
    • NEURAL NETWORKS PROJECT-GESTURE RECOGNITION
    •   REINFORCEMENT LEARNING
    • CLASSICAL REINFORCEMENT LEARNING
    • ASSIGNMENT -CLASSICAL
    • DEEP REINFORCEMENT LEARNING
    • REINFORCEMENT LEARNING PROJECT
    •   CAPSTONE
    • DEPLOYMENT
    • CAPSTONE

Student Reviews

Ridhu

25/01/2023 11:12:50pm

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11/12/2022 10:03:21am

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26/11/2022 11:14:23am

I am a student of python in Edu Tech Boom, It is a good place for learning and improving tech skills . and our trainer anil sir guides us at every level.

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