Artificial Intelligence (AI) Online Training Course (2025)

Name: Artificial Intelligence Certification Course
Item: Artificial Intelligence Certification Course
Rating: 5
Author: Muralidhar Gaddam

Introduction to Text Mining and NLP

Topics:

Overview of Text Mining
Need of Text Mining
Natural Language Processing (NLP) in Text Mining
Applications of Text Mining
OS Module
Reading, Writing to text and word files
Setting the NLTK Environment
Accessing the NLTK Corpora

Hands-on:

Install NLTK Packages using NLTK Downloader
Accessing your operating system using the OS Module in Python
How to read json format, understand key-value pairs, and for that matter, understand uses of pkl files

Skills You will Learn

Reading & Writing .txt Files from/to your Local
Reading & Writing .docx Files from/to your Local
Working with the NLTK Corpora

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Extracting, Cleaning and Preprocessing Text

Topics:

Tokenization
Frequency Distribution
Different Types of Tokenizers
Bigrams, Trigrams & Ngrams
Stemming
Lemmatization
Stopwords
POS Tagging
Named Entity Recognition

Hands-on:

Regex, Word, Blankline, Sentence Tokenizers
Bigrams, Trigrams & Ngrams
Stopword Removal
UTF encoding, dealing with URLs, hashtags
POS Tagging
Named Entity Recognition (NER)

Skills You will Learn

Tokenization
Stopword Removal
UTF encoding
POS Tagging
Named Entity Recognition (NER)

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Analyzing Sentence Structure

Topics:

Syntax Trees
Chunking
Chinking
Context Free Grammars (CFG)
Automating Text Paraphrasing

Hands-on:

Parsing Syntax Trees
Chunking
Chinking
Automate Text Paraphrasing using CFG’s

Skills You will Learn

Chunking
Chinking
Automate Text Paraphrasing

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Text Classification-I

Topics:

Machine Learning: Brush Up
Bag of Words
Count Vectorizer
Term Frequency (TF)
Inverse Document Frequency (IDF)

Hands-on:

Demonstrate Bag of Words Approach
Working with CountVectorizer()
Using TF & IDF

Skills You will Learn

Bag of Words
CountVectorizer()
TF-IDF

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Introduction to Deep Learning

Topics:

What is Deep Learning?
Curse of Dimensionality
Machine Learning vs. Deep Learning
Use cases of Deep Learning
Human Brain vs. Neural Network
What is Perceptron?
Learning Rate
Epoch
Batch Size
Activation Function
Single Layer Perceptron

Hands-on:

Single Layer Perceptron

Skills You will Learn

Curse of Dimensionality
Single Layer Perceptron

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Getting Started with TensorFlow 2.0

Topics:

Introduction to TensorFlow 2.x
Installing TensorFlow 2.x
Defining Sequence model layers
Activation Function
Layer Types
Model Compilation
Model Optimizer
Model Loss Function
Model Training
Digit Classification using Simple Neural Network in TensorFlow 2.x
Improving the model
Adding Hidden Layer
Adding Dropout
Using Adam Optimizer

Hands-on:

Classifying handwritten digits using TensorFlow 2.0

Skills You will Learn

Installing and Working with TensorFlow 2.0

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Convolution Neural Network

Topics:

Image Classification Example
What is Convolution
Convolutional Layer Network
Convolutional Layer
Filtering
ReLU Layer
Pooling
Data Flattening
Fully Connected Layer
Predicting a cat or a dog
Saving and Loading a Model
Face Detection using OpenCV

Hands-on:

Saving and Loading a Model
Face Detection using OpenCV

Skills You will Learn

Image Classification using CNN
Face Detection using OpenCV

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Regional CNN

Topics:

Introduction to Business Intelligence
Self-Service Business Intelligence (SSBI)
Introduction to Power BI
Traditional BI vs. Power BI
Power BI vs. Tableau vs. QlikView
Uses of Power BI
The Flow of Work in Power BI
Working with Power BI
Basic Components of Power BI
Comparison of Power BI Version
Introduction to Building Blocks of Power BI
Data model and importance of Data Modeling

Hands-on:

Installation of Power BI

Skills You will Learn

Transfer Learning
Object Detection
Mask R-CNN

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Boltzmann Machine & Autoencoder

Topics:

What is Boltzmann Machine (BM)?
Identify the issues with BM
Why did RBM come into picture?
Step by step implementation of RBM
Distribution of Boltzmann Machine
Understanding Autoencoders
Architecture of Autoencoders
Brief on types of Autoencoders
Applications of Autoencoders

Hands-on:

Implement RBM
Simple encoder

Skills You will Learn

RBM
Autoencoders

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Boltzmann Machine & Autoencoder

Topics:

Which Face is Fake?
Understanding GAN
What is Generative Adversarial Network?
How does GAN work?
Step by step Generative Adversarial Network implementation
Types of GAN
Recent Advances: GAN

Hands-on:

Implement Generative Adversarial Network

Skills You will Learn

Generative

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Emotion and Gender Detection (Self-paced)

Topics:

Where do we use Emotion and Gender Detection?
How does it work?
Emotion Detection architecture
Face/Emotion detection using Haar Cascade
Implementation on Colab

Hands-on:

Implement Emotion and Gender Detection

Skills You will Learn

Emotion and Gender Detection

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Introduction RNN and GRU (Self-paced)

Topics:

Issues with Feed Forward Network
Recurrent Neural Network (RNN)
Architecture of RNN
Calculation in RNN
Backpropagation and Loss calculation
Applications of RNN
Vanishing Gradient
Exploding Gradient
What is GRU?
Components of GRU
Update gate
Reset gate
Current memory content
Final memory at current time step

Hands-on:

Implement COVID RNN GRU

Skills You will Learn

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LSTM (Self-paced)

Topics:

What is LSTM?
Structure of LSTM
Forget Gate
Input Gate
Output Gate
LSTM architecture
Types of Sequence-Based Model
Sequence Prediction
Sequence Classification
Sequence Generation
Types of LSTM
Vanilla LSTM
Stacked LSTM
CNN LSTM
Bidirectional LSTM
How to increase the efficiency of the model?
Backpropagation through time
Workflow of BPTT

Hands-on:

Intent Detection using LSTM

Skills You will Learn

LSTM
Sequence Prediction
Sequence Classification
Sequence Generation

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Auto Image Captioning Using CNN LSTM (Self-paced)

Topics:

Auto Image Captioning
COCO dataset
Pre-trained model
Inception V3 model
Architecture of Inception V3
Modify last layer of pre-trained model
Freeze model
CNN for image processing
LSTM or text processing

Hands-on:

Auto Image Captioning

Skills You will Learn

Auto Image Captioning
CNN for image processing
LSTM or text processing

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Developing a Criminal Identification and Detection Application Using OpenCV (Self-paced)

Topics:

Why is OpenCV used?
What is OpenCV
Applications
Demo: Build a Criminal Identification and Detection App

Hands-on:

Build a Criminal Identification and Recognition app on Streamlit.

Skills You will Learn

OpenCV
Project Implementation with OpenCV

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TensorFlow for Deployment (Self-paced)

Topics:

Use Case: Amazon’s Virtual Try-Out Room.
Why Deploy models?
Model Deployment: Intuit AI models
Model Deployment: Instagram’s Image Classification Models
What is Model Deployment
Types of Model Deployment Techniques
TensorFlow Serving
Browser-based Models
What is TensorFlow Serving?
What are Servables?
Demo: Deploy the Model in Practice using TensorFlow Serving
Introduction to Browser based Models
Demo: Deploy a Deep Learning Model in your Browser.

Hands-on:

Learn and build a program that Detects Faces using your webcam using OpenCV.
Learn Hyper parameter tuning techniques in Keras on a Fashion Dataset.
Build and deploy a model using TensorFlow Serving.
Build a neural network model for Handwritten digits use activation function, batch size, Optimizer and learning rate for betterment of you model.
Build a Object detection model and detection is done by providing a video the model accurately identifies the objects that are depicted in the video.

Skills You will Learn

Deploying model with Tensorflow

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Text Classification-II (Self-paced)

Topics:

Converting text to features and labels
Multinomial Naive Bayes Classifier
Leveraging Confusion Matrix

Hands-on:

Converting text to features and labels
Demonstrate text classification using Multinomial NB Classifier
Leveraging Confusion Matri

Skills You will Learn

Converting text to features and labels
Text classification
Confusion Matrix

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In Class Project (Self-paced)

Topics:

Sentiment Classification on Movie Rating Dataset

Hands-on:

Implement all the text processing techniques starting with tokenization
Express your end to end work on Text Mining
Implement Machine Learning along with Text Processing

Skills You will Learn

Sentiment Analysis

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What is the AI Engineering Course?

Edureka’s Artificial Intelligence Course is well researched amalgamation of Natural Language Processing and Deep Learning, specifically designed for professionals and beginners to meet the industry standards. This course gives you an in-depth understanding of Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing using Python’s NLTK package, CNN, RCNN, RNN, LSTM, RBM, and their implementation using TensorFlow 2.0 package. You will learn to build real-time projects on NLP and Deep Learning, to make you industry-ready and help you to kickstart your career in this domain.

What are the prerequisites for this Artificial Intelligence Training?

Prior knowledge of Python and Machine Learning will be helpful but not at all mandatory. To refresh your skills in Python and ML, we will provide self-paced videos absolutely free as prerequisites in your LMS.

Why take up the Artificial Intelligence Online Certification Course?

The demand for AI engineers is increasing rapidly and is expected to continue growing in the future, driven by the increasing adoption of AI technologies in various industries and the growing importance of AI skills in the job market.

There are many reasons why someone might want to take up an online artificial intelligence course. Here are a few:

Career advancement: Artificial intelligence is one of the fastest-growing fields in technology today, and there is a high demand for skilled professionals in this area. By taking an AI course, you can increase your skills and knowledge and make yourself more valuable to employers.
Stay up-to-date: The field of artificial intelligence is rapidly evolving, with new technologies and techniques being developed all the time. By taking an AI course, you can stay up-to-date with the latest trends and developments in the field.
Learn from experts: You will be taught by experts in the field, giving you access to their knowledge and experience. This can be invaluable in helping you understand complex topics and gain practical skills.

How will Artificial Intelligence help your career?

The field of artificial intelligence (AI) is rapidly growing and is expected to continue growing in the coming years. AI is being used in many industries such as healthcare, finance, education, and more. With the increasing adoption of AI, there is a high demand for professionals with the necessary skills and knowledge to work in this field.

Here are some ways AI career growth is happening:

Increased job opportunities: There is a growing demand for AI professionals in both technical and non-technical roles. Technical roles include AI engineers, data scientists, machine learning engineers, and software developers, while non-technical roles include AI project managers, AI consultants, and AI analysts.
Advancements in technology: As AI technology advances, there are new opportunities for AI professionals to develop new applications and solutions that can solve complex problems.
Emerging subfields: There are emerging subfields within AI, such as explainable AI, AI ethics, and AI security, which provide new opportunities for AI professionals to specialize and grow their careers.
Continuous learning and development: AI is a constantly evolving field, and AI professionals must continuously learn and develop new skills to stay up-to-date with the latest advancements.

Overall, the field of AI provides many opportunities for career growth and development, and there is a high demand for skilled professionals in this field. Enroll in this Artificial Intelligence Certification training today.

Who should take up this Artificial Intelligence Course?

The Artificial Intelligence course is suitable for anyone who wants to stay up-to-date with the latest advances in AI and wants to build the skills needed to develop and deploy intelligent systems.

This course will be ideal for the following professionals.

Freshers
Python Developers
Researchers
Data Scientists
Data Analysts
Machine Learning Engineers
NLP Engineers
Software Testers
Software Developers

If you are one of the above, then do not hesitate to talk to our assistant team and enroll in our AI Course training today.

What are the basic skills of a Artificial Intelligence Engineer?

Artificial Intelligence (AI) is a broad field with many subfields, and the skills required for an AI engineer can vary depending on the specific area of expertise. However, there are some basic skills that most AI engineers should possess:

Strong Programming Skills: AI engineers need to have a strong foundation in programming languages such as Python, C++, Java, or R. This includes knowledge of data structures, algorithms, and object-oriented programming.
Machine Learning: AI engineers must have a solid understanding of the concepts and algorithms of machine learning. This includes knowledge of supervised and unsupervised learning, deep learning, and natural language processing (NLP).
Data Structures and Algorithms: A deep understanding of data structures and algorithms is essential for designing and implementing efficient algorithms for large data sets. This also includes knowledge of big data technologies and distributed computing.
Statistics and Probability: Knowledge of statistics and probability is essential for understanding and designing machine learning algorithms. AI engineers need to know concepts like hypothesis testing, regression analysis, and Bayesian networks.
Problem Solving: AI engineers must have strong problem-solving skills to design and implement complex AI systems. They must be able to identify problems, break them down into smaller components, and develop solutions.
Creativity: AI engineers must be creative thinkers to develop novel solutions to complex problems. They should be able to think outside the box and come up with innovative ideas.
Ethics and Accountability: AI engineers must understand the ethical implications of their work and the impact it has on society. They must ensure their AI systems are transparent, explainable, and accountable.

What is the main focus of Edureka’s AI Training Course?

Edureka’s Artificial Intelligence Course enables you to move ahead in your career by helping you get skilled with the fundamentals of AI. The AI course focuses on providing hands-on experience to make you ready for any AI related opportunity.

What will I learn from this Artificial Intelligence Online Training Course?

Learn the fundamentals of Natural Language Processing (NLP), sentiment analysis, language translation, text summarization, deep learning, convolutional neural networks, recurrent neural networks, and autoencoders. Additionally, you will be working with the OpenCV library, object detection, image segmentation, and image classification along with various real-life projects.

What are the system requirements for this Artificial Intelligence Course?

The system requirements for this AI Course

A system with an Intel i3 processor or above
A minimum of 4GB RAM (8GB or above is recommended for faster processing)
50 GB HDD Storage
Operating system: 32-bit or 64-bit

How will I execute the practicals in this Artificial Intelligence Online Course?

You will execute your Assignments/Case Studies using Python Jupyter Notebook/Google Colab. Detailed step-by-step installation guides are available on the LMS. In case you come across any doubt, the 24*7 support team will promptly assist you.

How much does an AI course cost?

The cost of an AI course is INR 19,995, but you can get it at a discounted price of INR 17,995 and Save INR 2000. This offer is limited. You can also avail of No-Cost EMI, which starts at 5,999 / month.

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What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. It involves the development of algorithms and systems that enable machines to perform tasks that typically require human intelligence. These tasks can include reasoning, problem-solving, learning, perception, language understanding, and decision-making.

What is Deep Learning?

Deep Learning is a subset of machine learning that focuses on artificial neural networks and their ability to learn and make decisions in a manner similar to the human brain. It involves training deep neural networks with multiple layers to process and learn from large amounts of data, enabling these networks to perform complex tasks such as image and speech recognition, natural language processing, and more.

Can I attend a demo Artificial Intelligence session before enrollment?

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

Who are the instructors for this Artificial Intelligence Course?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

How can I become an AI Engineer?

To become an AI engineer, you can follow these steps:

Learn programming: Start with languages like Python, Java, or C++, and gain proficiency in data structures and algorithms.

Understand mathematics and statistics: Study linear algebra, calculus, probability, and statistics to grasp the foundations of AI.

Master machine learning: Learn about various ML algorithms, techniques, and frameworks such as TensorFlow or PyTorch.

Gain practical experience: Work on real-world projects, participate in Kaggle competitions and build a portfolio to showcase your skills.

Specialize in AI subfields: Explore areas like natural language processing, computer vision, or reinforcement learning.

Continuous learning: Stay updated with the latest advancements and research in AI through online courses, tutorials, and academic papers.

What if I have more queries after this AI Course?

Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co

What if I miss a Artificial Intelligence Training class?

You will never miss a lecture at Edureka! You can choose either of the two options:

View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.

Will I get placement assistance after this AI Course?

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

Which is the best AI Online Course for beginners?

The Edureka Artificial Intelligence Course is highly recommended for beginners. It provides a comprehensive learning experience, covering basic to advanced concepts of artificial intelligence. The course includes a focus on Python, a widely used programming language in AI.

Where can I learn artificial intelligence?

Edureka is the best place to learn artificial intelligence. It focuses on Specific topics within AI, such as NLP, deep learning, or TensorFlow.

What is the course duration of the AI Training Course?

The duration of the AI Course is 36 hours. The online class batches are scheduled on weekends.

What online courses that are available on Edureka will help me to learn about Artificial Intelligence?

Some of the top courses are

What is the Salary of an AI Engineer in India?

The salary of an AI engineer in India can vary depending on factors such as experience, skillset, location, industry, and the organization's size. On average, AI engineers in India can expect to earn a salary ranging from INR 5 lakh to INR 20 lakh per year. However, it's important to note that these figures are approximate and can vary significantly based on the factors mentioned earlier. Highly skilled and experienced AI engineers working in top tech companies or specialized fields may command higher salaries, potentially exceeding INR 20 lakh per year. Additionally, AI engineers with advanced degrees or certifications and those with expertise in specific subfields of AI, such as natural language processing or computer vision, may have better salary prospects. It's essential to refer to up-to-date salary surveys and resources for the most accurate and recent information on AI engineer salaries in India.

What kind of projects are included as part of the AI Certification Course?

As part of AI Courseto become an AI engineer, you may work on various projects focusing on different aspects of AI. Some common project areas include:

Machine Learning: Projects involving training models for classification, regression, or recommendation systems. Examples could include building a spam email classifier or predicting house prices.

Natural Language Processing (NLP): Projects related to language understanding and generation, such as sentiment analysis, chatbots, or language translation systems.

Computer Vision: Projects that deal with image or video analysis, such as object detection, facial recognition, or autonomous driving systems.

Reinforcement Learning: Projects centred around training agents to make decisions in dynamic environments, like teaching a robot to navigate a maze or playing complex games.

Data Analysis: Projects involving exploratory data analysis, data preprocessing, and feature engineering, often using statistical techniques and visualizations.

These projects aim to provide hands-on experience in applying AI techniques to solve real-world problems and help you develop practical skills and understanding in the field of AI engineering.

What are the applications of artificial intelligence?

Artificial Intelligence (AI) has a wide range of applications across various industries like healthcare, finance, automotive, retail, education, manufacturing, entertainment, cybersecurity, agriculture, and marketing to enhance efficiency, automation, etc.

What are the advantages of Artificial Intelligence?

The advantages of Artificial Intelligence include increased efficiency, automation of repetitive tasks, enhanced decision-making, reduced human error, 24/7 operations, improved productivity, faster data processing, and the ability to provide valuable insights for innovation and problem-solving across industries.

What are the types of artificial intelligence?

The types of Artificial Intelligence are categorized into three main types:

Narrow AI, General AI, and Super AI.

What is AI with real time example?

A real-time example is virtual assistants like Siri or Google Assistant, which use AI to understand voice commands, process language, and provide relevant responses or perform actions like setting reminders or answering questions. These AI systems learn from interactions and improve their responses over time.

Which app has the best AI?

The best AI apps include Google Assistant for voice recognition, ChatGPT for text generation, Siri for iOS integration, Tesla Autopilot for driving assistance, IBM Watson for analytics, Replika as an AI companion, and Prisma for photo art. The choice depends on specific user needs.

Which AI tool is the best?

The best AI tool varies by use case but includes TensorFlow for deep learning, OpenAI's GPT for natural language processing, IBM Watson for analytics, and H2O.ai for machine learning. Each excels in specific areas, so the ideal choice depends on project requirements and goals.

What is the future for Artificial Intelligence?

The future of Artificial Intelligence promises enhanced automation, personalized applications in healthcare, education, and finance, and increased focus on ethical development. AI will play a crucial role in addressing global challenges like climate change, optimizing systems, and improving efficiency, significantly shaping how we work and interact with technology.

What is artificial intelligence software?

Artificial intelligence software refers to programs and applications that enable machines to perform tasks typically requiring human intelligence, such as learning, reasoning, problem-solving, and natural language processing. Examples include machine learning frameworks like TensorFlow, AI-powered chatbots, and predictive analytics tools used in various industries for data-driven decision-making.

What is NLP in AI?

Natural Language Processing in AI enables machines to understand, interpret, and respond to human language, facilitating tasks like translation, sentiment analysis, chatbots, and voice recognition.

What is the most popular algorithm in AI?

The most popular algorithms in AI include neural networks for deep learning, Convolutional Neural Networks (CNNs) for image tasks, and Recurrent Neural Networks (RNNs) for sequence data processing.

What is the main feature of AI?

The main feature of AI is its ability to learn from data, enabling machines to adapt, make decisions, and perform tasks that typically require human intelligence, such as reasoning and problem-solving.

View course curriculum

Testimonial Reviews

Piyush MahiskeyIT Analyst

The teacher taught the basic concepts very well even to those who were new to Python. A very crystal ... Read More

Saivikram GaliiOS Developer

I have gone through the Artificial Intelligence Certification Training course with edureka, it was ... Read More

Tejinder SinghPGDCA, MSc(IT), MCA, M-tech(IT), Phd(CS)*, Lecturer, Baba Farid College, Punjab

There is a plethora of online training material available for Android; the reason I chose Edureka is ... Read More

Souvik KunduLearning to code the web, big data & cloud computing. Aspiring Developer

I'm currently enrolled in a lot of courses offered at Edureka, so I'm attending live classes and usi ... Read More

Rahul KushwahDevops Software Developer and AWS Certified Solutions Architect

Edureka is BEST in provide e-learning courses for all software programs including latest technologie ... Read More

Muralidhar GaddamDevOps Professional, Project/Program Management Corporate Trainer

I got full value from Edureka's DevOps course. I had to come out of my comfort zone as I was expecti ... Read More

Video Reviews

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Artificial Intelligence Certification Course

Why should you take Artificial Intelligence Certification Course?

Instructor-led Artificial Intelligence Certification Course live online classes

Financing Options

Artificial Intelligence Course Curriculum

Introduction to Text Mining and NLP

Extracting, Cleaning and Preprocessing Text

Analyzing Sentence Structure

Text Classification-I

Introduction to Deep Learning

Getting Started with TensorFlow 2.0

Convolution Neural Network

Regional CNN

Boltzmann Machine & Autoencoder

Boltzmann Machine & Autoencoder

Emotion and Gender Detection (Self-paced)

Introduction RNN and GRU (Self-paced)

LSTM (Self-paced)

Auto Image Captioning Using CNN LSTM (Self-paced)

Developing a Criminal Identification and Detection Application Using OpenCV (Self-paced)

TensorFlow for Deployment (Self-paced)

Text Classification-II (Self-paced)

In Class Project (Self-paced)

AI Training Course Description

What is the AI Engineering Course?

What are the prerequisites for this Artificial Intelligence Training?

Why take up the Artificial Intelligence Online Certification Course?

How will Artificial Intelligence help your career?

Who should take up this Artificial Intelligence Course?

What are the basic skills of a Artificial Intelligence Engineer?

What is the main focus of Edureka’s AI Training Course?

What will I learn from this Artificial Intelligence Online Training Course?

What are the system requirements for this Artificial Intelligence Course?

How will I execute the practicals in this Artificial Intelligence Online Course?

How much does an AI course cost?

Testimonial Reviews

Video Reviews

Artificial Intelligence Online Course FAQs

What is Artificial Intelligence?

What is Deep Learning?

Can I attend a demo Artificial Intelligence session before enrollment?

Who are the instructors for this Artificial Intelligence Course?

How can I become an AI Engineer?

What if I have more queries after this AI Course?

What if I miss a Artificial Intelligence Training class?

Will I get placement assistance after this AI Course?

Which is the best AI Online Course for beginners?

Where can I learn artificial intelligence?

What is the course duration of the AI Training Course?

What online courses that are available on Edureka will help me to learn about Artificial Intelligence?

What is the Salary of an AI Engineer in India?

What kind of projects are included as part of the AI Certification Course?

What are the applications of artificial intelligence?

What are the advantages of Artificial Intelligence?

What are the types of artificial intelligence?

What is AI with real time example?

Which app has the best AI?

Which AI tool is the best?

What is the future for Artificial Intelligence?

What is artificial intelligence software?

What is NLP in AI?

What is the most popular algorithm in AI?

What is the main feature of AI?

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