GET IN TOUCH

Flat 30% Discount for all our Brave Veteran on all IT Trainings + 1 Self paced Training | OFFER ENDING IN :  GRAB NOW

Artificial Intelligence Course Certification

The Advanced Artificial Intelligence Course from CertHippo 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.

monetization_on

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.

8.6K + satisfied learners.     Reviews

4.2
Google Review
3.8
Trustpilot Reviews
3.2
Sitejabber Reviews
2.9
G2 Review

Instructor-led live online classes

Artificial Intelligence Course Certification

Live online Training (Weekday/ Weekend)

$850  $549

Enroll Now

Why Enroll In Artificial Intelligence 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.

Artificial Intelligence Training Features

Live Interactive Learning

  World-Class Instructors

  Expert-Led Mentoring Sessions

  Instant doubt clearing

Lifetime Access

  Course Access Never Expires

  Free Access to Future Updates

  Unlimited Access to Course Content

24x7 Support

  One-On-One Learning Assistance

  Help Desk Support

  Resolve Doubts in Real-time

Hands-On Project Based Learning

  Industry-Relevant Projects

  Course Demo Dataset & Files

  Quizzes & Assignments

Industry Recognized Certification

  CertHippo Training Certificate

  Graded Performance Certificate

  Certificate of Completion

Cloud

  Preconfigured Lab Environment

  Infrastructure with Tools and Software

  Single Sign-On

About your AWS Course

AWS Solutions Architect Course Skills Covered

Managing Security

Designing Data Storage Solutions

Monitoring Cloud Solutions

Designing Resilient AWS Solutions

AWS Cloud Cost Optimization

Designing Identity Solutions

Artificial Intelligence Course Curriculum

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

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)

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

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
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

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

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

Topics

  • Regional-CNN
  • Selective Search Algorithm
  • Bounding Box Regression
  • SVM in RCNN
  • Pre-trained Model
  • Model Accuracy
  • Model Inference Time
  • Model Size Comparison
  • Transfer Learning
  • Object Detection – Evaluation
  • mAP
  • IoU
  • RCNN – Speed Bottleneck
  • Fast R-CNN
  • RoI Pooling
  • Fast R-CNN – Speed Bottleneck
  • Faster R-CNN
  • Feature Pyramid Network (FPN)
  • Regional Proposal Network (RPN)
  • Mask R-CNN

Hands-on/Demo

  • Transfer Learning
  • Object Detection

Skills

  • Transfer Learning
  • Object Detection
  • Mask R-CNN

Topics

  • What is Boltzmann Machine (BM)?
  • Identify the issues with BM
  • Why did RBM come into the 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/Demo

  • Implement RBM
  • Simple encoder

Skills

  • RBM
  • Autoencoders

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

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
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/Demo
  • Implement COVID RNN GRU
Skills
  • RNN
  • GRU

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/Demo

  • Intent Detection using LSTM

Skills

  • LSTM
  • Sequence Prediction
  • Sequence Generation

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

Topics

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

Hands-on/Demo

  • Build a Criminal Identification and Recognition app on Streamlet.

Skills

  • OpenCV
  • Project Implementation with OpenCV

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/Demo

  • 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

  • Deploying model with Tensorflow

Topics

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

Hands-on/Demo

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

Skills

  • Converting text to features and labels
  • Text classification
  • Confusion Matrix

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
View More

Free Career Counselling

We are happy to help you 24/7

Please Note : By continuing and signing in, you agree to certhippo’s Terms & Conditions and Privacy Policy.

Certification

  • 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.

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.

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.


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.

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.


View More

Artificial Intelligence Online Training FAQs

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.


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.


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.


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.


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.

Just give us a CALL at +1 302 956 2015 OR email at info@certhippo.com


  • 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.

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.


View More

Artificial Intelligence Course Description

What is the Artificial Intelligence Course?

Natural Language Processing and Deep Learning are combined in the well-researched CertHippo 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 CertHippo Artificial Intelligence Course emphasize most?

By assisting you in becoming knowledgeable about the foundations of AI, the CertHippo 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.


View More

Selenium Certification

  • 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.

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.

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.


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.

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.


Similar Courses

Recently Viewed

Certhippo is a high end IT services, training & consulting organization providing IT services, training & consulting in the field of Cloud Coumputing.

CertHippo 16192 Coastal Hwy, Lewes, Delaware 19958, USA

CALL US : +1 302 956 2015 (USA)

EMAIL : info@certhippo.com