Expert Programmes

Artificial Intelligence Engineer Online Training Programme

(0 review)
All course fees are in USD)


Course Description

The Artificial Intelligence course, collaborated with IBM through Simplilearn,  introduces learners to blended learning and prepares them to be specialists in AI and Data Science. This AI course will prepare learners for careers in Artificial Intelligence and Data Analytics


About IBM

IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018).  This online course introduces learners to integrated blended learning, making them experts in Artificial Intelligence and Data Science. The AI courses designed in collaboration with IBM will make students industry-ready for Artificial Intelligence and Data Science job roles.

IBM is a leading cognitive solutions and cloud platform company, headquartered in New York of US, offering a plethora of technology and consulting services.

Each year, IBM invests about US$6 billion in research and development and has achieved five Nobel prizes, nine US National Medals of Technology, five US National Medals of Science, six Turing Awards, and 10 Inductions in US Inventors Hall of Fame.


Offered in Partnership with


Co-Developed by
IBM / Simplilearn


Course Delivery
  • Online self-paced learning (10+ hours)
  • Virtual classroom training (150+ hours)

Total: 160+ hours online blended learning


  • Total 211 hours online blended learning (19 hours self-paced learning & 192 hours of instructor-led training)
  • Real-life projects providing hands-on industry training
  • 10 In-demand skills
  • Portfolio-worthy capstone demonstrating mastered concepts


Skills to be Learned

You will be able to demonstrate the following ability after completing this Artificial Intelligence online training:

  • Learn Artificial Intelligence’s concept, purpose, domain breadth, phases, implementations, and impacts.
  • Create real-world projects, games, prediction models, logic constraint satisfaction concerns, experience and understanding systems, probabilistic models, and agent decision-making skills using your artificial intelligent machines and models.
  • Learn basic programming features and technicalities, such as data types, tuples, lists, arrays, basic operators, and functions.
  • Learn how to develop your Python programs and use the Jupyter notebook to analyze fundamental data.
  • Learn about data wrangling, data exploration, data visualization, hypothesis creation, and testing procedures in Data Science.
  • Use the NumPy and SciPy packages for high-level mathematical and technical computing and the Pandas package for data analysis.
  • Learn about supervised and unsupervised learning methods such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline, recommendation engines, and time series modeling.
  • Understand TensorFlow’s core principles, functions, operations, and the execution pipeline.
  • CNN, artificial neural networks, training deep RNN networks, and high-level NLP interfaces are among the advanced issues in AI.


Tools Covered in the Course
  • Python
  • TensorFlow
  • Keras
  • Django
  • Flask
  • OpenCV
  • NLTK
  • OCR
  • Scikit Learn


Award upon Successful Completion

Upon completion of this Online Program, you will receive the certificate from IBM and Simplilearn respectively. The certificates will testify to your skills as an expert in artificial intelligence.


Awarding Organisations
IBM / Simpliearn



Artificial Intelligence Engineer


Learning Outcomes
  • Learn about major applications of Artificial Intelligence across various use cases across various fields like customer service, financial services, healthcare, etc.
  • Implement classical Artificial Intelligence techniques such as search algorithms, neural networks, and tracking.
  • Gain the ability to apply Artificial Intelligence techniques for problem solving and explain the limitations of current Artificial Intelligence techniques.
  • Master skills and tools used by the most innovative Artificial Intelligence teams across the globe as you delve into specializations, and gain experience solving real-world challenges.
  • Design and build your own intelligent agents and apply them to create practical Artificial Intelligence projects including games, Machine Learning models, logic constraint satisfaction problems, knowledge based systems, probabilistic models, agent decision-making functions and more.
  • Understand concepts of TensorFlow, its main functions, operations, and the execution pipeline.
  • Understand and master concepts and principles of Machine Learning, including its mathematical and heuristic aspects.
  • Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces.
  • Learn to deploy deep learning models on Docker, Kubernetes, and in serverless environments (cloud)
  • Understand fundamentals of Natural Language Processing using the most popular library; Python’s Natural Language Toolkit (NLTK).



Real-life projects in various areas are included in this Artificial Intelligence course co-developed with IBM. These projects are intended to help you grasp essential AI topics like supervised and unsupervised learning, reinforcement learning, support vector machines, deep learning, TensorFlow, neural networks, convolutional neural networks, and recurrent neural networks.

This Artificial Intelligence Certification training includes a capstone assignment that allows you to review principles learned so far. You’ll take specialized guided classes to develop a high-quality industrial project that addresses a real-world problem. This AI course capstone project will cover everything from exploratory data analysis to model construction and fitting. You will employ cutting-edge AI-based supervised and unsupervised algorithms such as Regression, Multinomial Naive Bayes, SVM, Tree-based algorithms, and NLP in the topic of your choice to complete this capstone project. You will receive a capstone credential for completing the project. Still, you will also have a project to present to future employers as evidence of your learning from this Artificial Intelligence course.


  • Project 1


To reduce social hatred and negativity, create a model that employs natural language processing and machine learning to recognize inappropriate tweets that should be removed from the Twitter site.

  • Project 2


Amazon Prime videos’ movie reviews are included in data collection. Analyze the Amazon customer movie reviews data set and create a Machine Learning recommendation system that assigns scores to each user.

  • Project 3


Mercedes wants to reduce time spent on its test bench to reduce its time to bring a product (car) to market. Create and optimize a Machine Learning algorithm to solve this challenge.

  • Project 4


Create a predictive model to predict sales for Walmart stores while taking special discount events into account. Examine how sales are affected by macroeconomics variables such as the CPI and unemployment rate as features.

  • Project 5


Comcast intends to increase customer happiness by identifying and addressing issue areas and is looking for solutions that might be implemented.

  • Project 6


Based on the data set supplied, ML engineers must do data analysis on Amazon user evaluations of various items and forecast sentiment or satisfaction based on feature or review content.

  • Project 7


The banking industry is the most prevalent employer of data scientists. Scammers that try to fool the system are continuously targeting it. Credit card businesses must be able to discover illicit credit card frauds, notwithstanding the difficulty of precisely recognizing fraudulent and illegal activities. Several methodologies, such as classification with overfitting, unsupervised detection approaches, and heuristics, must be used to achieve maximum accuracy in detecting fraud.

  • Project 8


The most significant aspect of managing the retail supply chain is demand forecasting. Professionals must grasp Data Science and ensemble methodologies to do so efficiently. For the following month, you must forecast daily sales for each store.


Who Should Enrol
  • Individuals with interest in working as an AI or Machine Learning Engineer.
  • Analytical managers supervise a group of analysts.
  • Data architects who want to learn about artificial intelligence systems and algorithms.
  • Data analysts are interested in working in machine learning or artificial intelligence.
  • Professionals interested in artificial intelligence or machine learning as a profession.
  • Experts wish to improve their understanding of their fields by using Artificial Intelligence.
  • Graduates looking to build a career in Artificial Intelligence and Machine Learning


Participants in this AI course should know Python programming concepts and basic statistical knowledge to understand the essential Machine Learning and AI concepts.


Course Overview
  • Course 1 – Introduction to Artificial Intelligence
  • Course 2 – Data Science with Python
  • Course 3 – Machine Learning
  • Course 4 – Deep Learning with Keras and TensorFlow
  • Course 5 – AI Capstone Project


  • Python for Data Science
  • Advanced Deep Learning and Computer Vision
  • Natural Language Processing (NLP)
  • Industry Master Class – Artificial Intelligence


Access Period of Course

1 year from date of enrolment


Customer Reviews
Bibhu Dash

BDA-Claims Analytics at American Family Insurance

…. it was recommended to me by a colleague. However, after putting in many hours in the live training, projects, quizzes, and reading materials, now I am feeling much more confident in my work environment. I am very pleased with the course and hope it will help me in my future career growth.


DeAngelo Kelly

Artificial Intelligence Engineer

After completing this course, I was considered for new AI projects at my company, and my salary increased by 39%….. flexible learning method helped me manage my job simultaneously while studying.


Leena Jayamohan

Founder & Senior Consultant

I took this program, which consisted of multiple classes. Overall the teachers knew the subject and covered what was promised. The industry-related projects were excellent, and it helped put into practice what we learned in the class. I would recommend these classes to anyone planning to enter the Data Analytics field.


Sajitha Smiley Masilla Mony


The course curriculum was beneficial in real-world scenarios and was up-to-date. The faculties are skillful and well experienced. The class sessions are very interactive, and the faculties are always ready to clear our doubts to their best. Also, the flexible class helps us to learn the same course with other faculty and gain more knowledge.


Sneha Patil

I’ll give it a five-star rating…I enrolled in this course…the course content, shared drive, documents, pdf files, and — most importantly, the trainer — all are awesome…….


Venkatesan Sundaram

Senior Data Scientist

….. I learned a lot of new and interesting concepts. This course covered important AI topics including, image processing, deep learning, etc. The real life examples helped us understand the concepts better.


Indrakala Nigam Beniwal

Technical Consultant

……Thanks to the course teachers and others associated with designing such a wonderful learning experience.


Janani Varun

I would give a 5-star rating….. It helps me understand the content easily through online self-learning videos, and trainers assist us with their enriched knowledge, as well.


Mark Hayes

I had a great learning experience, overall. The course content met the quality standards and the instructors were highly knowledgeable. The live classes were engaging, too. After the course completion, I am now working as a consultant.


Vishwanath Ragha

The awesome learning experience……. So far, I have completed up to the Data Science with Python. All the courses are well structured with self-learning, live classes, and assessment. The trainers are good, connect to students, and answer questions. Happy learning.


Karan Pal Singh Bagga

Sr. Data Analyst

……The course content is excellent as compared to any other institute. Faculties are very experienced and skillful.


Shailender Kumar

The Deep Learning with Tensorflow was handled very well ….. – Mr. Shivendra Kumar. He took many pains to advance this highly technical course and answered all students’ questions (even multiple times) clearly without compromising the quality of the training. I recommend this course and the faculty.


Sudipta Samanta

The courses are well-structured with self-learning, live classes, projects & assessment. The trainers are well trained, connect well with the students, and are good at resolving your questions. The course content is excellent.

Course Features

  • Students 0 student
  • Max Students10000
  • Duration160 hour
  • Skill levelall
  • LanguageEnglish
  • Re-take course100000
  • Course 1 - Introduction to Artificial Intelligence

    This Introduction to Artificial Intelligence (AI) is designed to help learners decode the mystery of artificial intelligence and its business applications. This AI for beginners course provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics.

  • Course 2 Data Science with Python

    The Data Science with Python course provides a complete overview of Data Analytics tools and techniques using Python. Learning Python is a crucial skill for many Data Science roles. Acquiring knowledge in Python will be the key to unlock your career as a Data Scientist.

  • Course 3 - Machine Learning

    Explore the concepts of Machine Learning and understand how it’s transforming the digital world. An exciting branch of Artificial Intelligence, this Machine Learning certification online course will provide the skills you need to become a Machine Learning Engineer and unlock the power of this emerging field.

  • Course 4 - Deep Learning with Keras and TensorFlow

    This Deep Learning course with Tensorflow certification training is developed by industry leaders and aligned with the latest best practices. You’ll master deep learning concepts and models using Keras and TensorFlow frameworks and implement deep learning algorithms, preparing you for a career as Deep Learning Engineer.

  • • Course 5 - AI Capstone Project

    Advanced Deep Learning and Computer Vision


0 total

Related Courses