Artificial Intelligence Course Certification

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Artificial Intelligence Course Certification

The Advanced Artificial Intelligence Course from EduCerts teaches you the fundamentals of text processing and text classification as well as significant ideas like tokenization, stemming, lemmatization, POS tagging, and many others. You will learn how to use the most recent TensorFlow 2.0 package in Python to implement well-known algorithms like CNN, RCNN, RNN, LSTM, and RBM. You will also learn how to perform image pre-processing, image classification, transfer learning, object detection, and computer vision. In order to meet the most recent industry demands and requirements, this course was carefully selected by industry experts after extensive research. Join the global revolution now to unleash the power of artificial intelligence and advance your career.

Why This Course

Every sector of the economy is being shaped by AI, which will continue to lead technological innovation for the foreseeable future.

The size of the global AI market, estimated at USD 136.55 billion in 2022, is predicted to increase to USD 1,597.1 billion by 2030, with a CAGR of 37.3% from 2023 to 2030.

According to salary.com, the base pay for a Lead AI Engineer is between 157,302 and 191,127 USD, with an average base pay of 170,265.

Why Enroll In Course?

The amount of data produced today, by both humans and machines, far exceeds the capacity of humans to comprehend, interpret, and base complex decisions on that data. All computer learning is based on artificial intelligence, which is also the future of all complex decision-making. It also enables organizations to improve core business processes. The best way to find a good job in this field that pays well is to obtain an AI certification.

Training Features

Live Interactive Learning

Lifetime Access

24x7 Support

Hands-On Project Based Learning

Industry Recognized Certification

Cloud

Course Curriculum

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/Demo

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

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

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/Demo

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

Skills

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

Analyzing Sentence Structure

Topics

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

Hands-on/Demo

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

Skills

Chunking
Chinking
Automate Text Paraphrasing

Text Classification-I

Topics

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

Hands-on/Demo

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

Skills

Bag of Words
CountVectorizer()
TF-IDF

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/Demo

Single Layer Perceptron

Skills

Curse of Dimensionality
Single Layer Perceptron

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/Demo

Classifying handwritten digits using TensorFlow 2.0

Skills

Installing and Working with TensorFlow 2.0

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/Demo

Saving and Loading a Model
Face Detection using OpenCV

Skills

Image Classification using CNN
Face Detection using OpenCV

Generative Adversarial Network(GAN)

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/Demo

Implement Generative Adversarial Network

Skills

Generative Adversarial Network

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/Demo

Implement Emotion and Gender Detection

Skills

Emotion and Gender Detection

Auto Image Captioning Using CNN LSTM (Self-paced)

Topics

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

Hands-on/Demo

Auto Image Captioning

Skills

Auto Image Captioning
CNN for image processing
LSTM or text processing

In Class Project (Self-paced)

Topics

Sentiment Classification on Movie Rating Dataset

Hands-on/Demo

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

Sentiment Analysis

Free Career Counselling

We are happy to help you 24/7

Certification

How can I unlock my EduCerts Artificial Intelligence Course Certificate?

You must make sure of the following in order to unlock your CertHippo Artificial Intelligence course completion certificate:
Take part in this artificial intelligence course to the fullest.
Examining and finishing the projects and quizzes listed.

Is Artificial Intelligence a good career option?

Yes, there are many opportunities for career growth and development in the rapidly expanding field of artificial intelligence (AI). A high demand for qualified professionals in this field results from the potential for AI to transform industries like healthcare, finance, transportation, and more.

AI offers a wide range of career options, including those as a researcher, consultant, data scientist, machine learning engineer, and more. These positions frequently call for a mix of hard and soft skills, including communication and problem-solving, in addition to technical skills like programming and data analysis

In addition, AI is a field that is constantly developing, with new tools and methods appearing all the time. This necessitates that AI professionals stay current with new developments and continue to learn throughout their careers, creating a stimulating and demanding work environment. Overall, a career in AI might be a great fit if you're passionate about solving problems and have a keen interest in technology.

How can beginners learn Artificial Intelligence?

Learning the capabilities and functionality of artificial intelligence (AI) requires appropriate guidance and a well-structured training path because the field is complex and rapidly evolving. Beginners can enroll in our training and obtain certificates to prove their proficiency in this field if they are interested in a career in Artificial Intelligence using Python.

What is the value of Artificial Intelligence Certification?

A certification in artificial intelligence (AI) is becoming more and more valuable on the job market today as companies from all sectors look to incorporate AI technology into their operations. Having an AI certification can help you stand out from other applicants and show prospective employers that you have the abilities and knowledge required to work with AI.

The following are some possible advantages of earning an AI certification:

Expertise: An AI certification can help you show that you are knowledgeable about a particular branch of AI technology, like machine learning or natural language processing.
Increased employment opportunities: Possessing an AI certification may make it possible for you to apply for jobs that demand an understanding of AI technology. Jobs in data analysis, software development, and other technical fields may fall under this category.
Greater potential for salary: In general, people with specialized technical skills—such as AI—can demand higher salaries than those who lack those skills. Your earning potential may increase with an AI certification.
Competitive advantage: When applying for jobs or pursuing business opportunities, having an AI certification can help you stand out from the competition.
Professional advancement: Earning an AI certification can help you stay current with emerging technologies and trends while continuing to learn and develop in your field.
Overall, earning an AI certification can help you advance your career and stay competitive in a job market that is rapidly changing.

What are the different job roles available after Artificial Intelligence Certification?

Our artificial intelligence course is intended to improve candidates' skills and gauge their level of knowledge. You will have access to a variety of job opportunities once you have earned this certification. AI Engineer, Data Scientist, NLP Engineer, Deep Learning Engineer, Machine Learning Engineer, and others are some of the most crucial job roles.

Online Training FAQs

What is Artificial Intelligence?

Artificial intelligence (AI) is the term used to describe how machines, particularly computer systems, simulate human intelligence processes. It entails the creation of algorithms and systems that allow machines to carry out operations that ordinarily call for human intelligence. Reasoning, problem-solving, learning, perception, language comprehension, and decision-making are some examples of these tasks.

What is Deep Learning?

Artificial neural networks' capacity to learn and make decisions in a way that resembles the human brain is the focus of the machine learning subset known as deep learning. Performing complex tasks like image and speech recognition, natural language processing, and other tasks that require large amounts of data requires training deep neural networks with multiple layers to process and learn from this data.

Can I attend a demo Artificial Intelligence session before enrollment?

To uphold the Quality Standards, we only allow a certain number of people to participate in live sessions. Therefore, unfortunately, it is not possible to participate in a live class without enrolling. However, you can watch a sample class recording, which will give you a clear understanding of how classes are run, the caliber of the instructors, and the level of participation in a class.

Who are the instructors for this Artificial Intelligence Course?

All of CertHippo's instructors are active members of the industry with a minimum of 10 to 12 years of relevant IT experience. They have received training from CertHippo and are subject matter experts who will give participants an amazing learning experience.

How can I become an AI Engineer?

These steps can be taken in order to become an AI engineer:

Learn how to program: Learn the fundamentals of data structures and algorithms by beginning with languages like Python, Java, or C++.
Knowing statistics and mathematics To understand the principles of AI, learn linear algebra, calculus, probability, and statistics.
Understanding machine learning Discover various ML frameworks, techniques, and algorithms like TensorFlow or PyTorch.
acquiring real-world experience Work on practical projects, take part in Kaggle challenges, and create a portfolio to display your abilities.
Focus on specific AI subfields: Investigate fields like reinforcement learning, computer vision, or natural language processing.

What if I miss a Artificial Intelligence Training class?

At CertHippo, you'll never miss a lecture! Choose from one of the following two possibilities:
Check out the class's recorded session in your LMS. You can join any other live batch to make up the missed session.

Will I get placement assistance after this AI Course?

We have added a resume builder tool to your LMS as a resource for you in this endeavor. You will now be able to make a successful resume in just 3 simple steps. These templates are yours to use in any number of roles and positions at any time. Simply sign in to your LMS and select the "create your resume" option.

Course Description

What is the Artificial Intelligence Course?

Natural Language Processing and Deep Learning are combined in the well-researched EduCerts Artificial Intelligence Course, which was created with professionals and novices in mind to meet industry standards. 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 are all topics covered in-depth in this course. You will learn to create real-time NLP and Deep Learning projects that will prepare you for the industry and help you launch a career in this field.

Why take up the Online Artificial Intelligence Course?

The increasing adoption of AI technologies across a variety of industries and the rising value of AI skills in the labor market are driving the demand for AI engineers, which is expected to continue growing in the future.

One might want to enroll in an online artificial intelligence course for a variety of reasons. To name a few:

Career advancement: One of the technology fields that is currently growing the fastest is artificial intelligence, and there is a significant need for qualified personnel in this field. You can improve your knowledge and skills and increase your marketability to employers by enrolling in an AI course.
Stay current: Artificial intelligence is a rapidly developing field, with new tools and methods being created all the time. You can keep up with the newest trends and advancements in the field by enrolling in an AI course.
Learn from professionals: You will receive instruction from professionals in the field, giving you access to their expertise and knowledge. This can be incredibly helpful in making sure you comprehend difficult concepts and develop useful skills.

How will Artificial Intelligence help your career?

Artificial intelligence (AI) is a rapidly expanding field that is predicted to keep expanding in the years to come. Numerous sectors, including healthcare, finance, education, and others, are utilizing AI. A high demand exists for professionals who have the necessary training and expertise to work in the field of artificial intelligence due to its growing uptake.

These are some ways that the field of AI is expanding:

Rising demand for AI professionals in both technical and non-technical roles has led to more job opportunities. AI project managers, AI consultants, and AI analysts are examples of non-technical roles while AI engineers, data scientists, machine learning engineers, and software developers are examples of technical roles.

Technology advancements: As AI technology develops, there are more opportunities for AI professionals to create innovative applications and solutions that can tackle challenging issues.

Emerging subfields: New opportunities for AI professionals to specialize and advance their careers are presented by emerging subfields within AI, including explainable AI, AI ethics, and AI security.

Continuous learning and skill development are necessary for AI professionals to keep up with the field’s rapid advancements. AI is a field that is constantly changing.

Overall, there is a high demand for qualified professionals in the field of AI and many opportunities for career growth and development. Enroll right away in this Artificial Intelligence Certification course.

What are the essential concepts covered in this Artificial Intelligence Course?

This artificial intelligence course covers a wide range of topics, including Deep Learning, TensorFlow, OpenCV, Natural Language Processing, Text Classification, Text Processing, Image Processing, Object Detection, and many others.

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?

Given the wide range of subfields in artificial intelligence (AI), an AI engineer’s skill set will depend on their area of specialization. However, the majority of AI engineers should have the following fundamental abilities:

Strong Programming Skills: Programming languages like Python, C++, Java, or R require a strong foundation for AI engineers. Data structures, algorithms, and object-oriented programming knowledge are all included in this.

Machine Learning: AI engineers need to have a firm grasp of the ideas and procedures underlying machine learning. This includes understanding of deep learning, natural language processing (NLP), and supervised and unsupervised learning.

Designing and putting into practice effective algorithms for big data sets requires a thorough understanding of data structures and algorithms. This also entails familiarity with distributed computing and big data technologies.

Probability and statistics: Understanding and creating machine learning algorithms require a thorough understanding of probability and statistics. Concepts like hypothesis testing, regression analysis, and Bayesian networks are essential knowledge for AI engineers.

To design and implement complex AI systems, AI engineers need to have strong problem-solving abilities. They must be able to recognize issues, deconstruct them into simpler parts, and create solutions.

Creativity: AI engineers need to think creatively to come up with new solutions to challenging issues. They ought to be able to think creatively and creatively outside the box.

Accountability and Ethics: AI engineers need to be aware of the moral ramifications of their work and the effects it has on society. They must guarantee that their AI systems are accountable, transparent, and comprehensible.

What are the prerequisites for this Artificial Intelligence Course?

Although not required, prior Python and machine learning knowledge will be useful. We will offer self-paced videos in your LMS as pre-requisites to help you brush up on your knowledge of Python and machine learning.

What does the EduCerts Artificial Intelligence Course emphasize most?

By assisting you in becoming knowledgeable about the foundations of AI, the EduCerts Artificial Intelligence Course gives you the opportunity to advance in your career. The AI course places a strong emphasis on giving you practical experience so you’ll be prepared for any AI-related opportunity.

How will this artificial intelligence course benefit me?

Learn the fundamentals of text summarization, sentiment analysis, language translation, deep learning, convolutional neural networks, recurrent neural networks, and autoencoders, as well as natural language processing (NLP). Along with various real-world projects, you will also work with the OpenCV library, object detection, image segmentation, and image classification.

What are the system requirements for this Artificial Intelligence Course?

The required hardware for this AI course
A computer with a processor from Intel i3 or higher
4GB RAM is the minimum requirement; 8GB or more is advised for faster processing.
50 GB HDD Storage
running program: 64-bit vs. 32-bit

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

You will use Google Colab and Python Jupyter Notebook to complete your assignments and case studies. On the LMS, you can find thorough step-by-step installation instructions. In the event that you have any questions, the team is available around-the-clock to help.