Artificial Intelligence Engineer – Master Certification Programme
(All course fees are in USD)
Artificial Intelligence is a branch of computer science that involves the development of computer systems that mimic a human brain and enable them to perform tasks that usually require human intelligence. Computers can be trained to accomplish tasks by processing large volumes of data and recognizing patterns in that data using different AI techniques.
This Artificial Intelligence Master’s Program covers the crucial skills you need for a successful career in artificial intelligence (AI). As you undertake your AI engineer training, you’ll master the concepts of deep learning, machine learning, natural language processing (NLP), plus the programming languages needed to
excel in an AI career with exclusive training and certification from IBM.
You will learn how to design intelligent models and advanced artificial neural networks and leverage predictive analytics to solve real-time problems in this course, in collaboration with IBM.
Developed /Co-Developed by
IBM & Simplilearn
IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students 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, offering a plethora of technology and consulting services.
Each year, IBM invests $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
- Online self-paced learning (19 hours)
- Virtual classroom training (192 hours)
Total: 211 hours online blended learning
- Total 211 hours online blended learning (19 hours self-paced learning & 192 hours of instructor-led training)
- 15+ Real-life projects providing hands-on industry training
- 20+ In-demand skills
- Portfolio-worthy capstone demonstrating mastered concepts
Skills to be Learned
- Understand the meaning, purpose, scope, stages, applications, and effects of Artificial Intelligence
- Design and build your own intelligent agents, applying them to create practical Artificial Intelligence projects, including games, machine learning models, logic constraint satisfaction problems, knowledge-based systems, probabilistic models, and agent decision-making functions
- Master the essential concepts of Python programming, including data types, tuples, lists, dicts, basic operators, and functions
- Learn how to write your own Python scripts and perform basic hands-on data analysis using Jupyter notebook
- Gain an in-depth understanding of Data Science processes: data wrangling, data exploration, data visualization, hypothesis building, and testing
- Perform high-level mathematical and technical computing using the NumPy and SciPy packages and data analysis with the Pandas package
- Master the concepts of supervised and unsupervised learning models, including linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline, recommendation engine, and time series modeling
- Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline
- Master advanced topics in Artificial Intelligence, such as convolutional neural networks, recurrent neural networks, training deep networks, and high-level interfaces
Award upon Successful Completion
Upon completion of this Master’s Program, you will receive the certificate from IBM and Simplilearn respectively. The certificates will testify to your skills as an expert in artificial intelligence.
IBM / Simpliearn
- Learn about the 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 the 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 the concepts of TensorFlow, its main functions, operations, and the execution pipeline.
- Understand and master the 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 the fundamentals of Natural Language Processing using the most popular library; Python’s Natural Language Toolkit (NLTK).
This Artificial Intelligence Engineer Master’s program co-developed by Simplilearn with IBM includes over 15 real-life, branded projects in different domains. These projects are designed to help you master the key concepts of Artificial Intelligence like supervised and unsupervised learning, reinforcement learning, support vector machines, Deep Learning, TensorFlow, neural networks, convolutional neural networks, and recurrent neural networks.
This AI Engineer Master’s Program includes a capstone project allowing you to revisit the concepts learned throughout the courses. You will go through dedicated mentored classes in order to create a high-quality industry project, solving a real-world problem.
The capstone project will cover key aspects from exploratory data analysis to model creation and fitting. To complete this capstone project, you will use cutting edge Artificial Intelligence-based supervised and unsupervised algorithms like Regression, Multinomial Naïve Bayes, SVM, Tree-based algorithms, and NLP in the domain of your choice. After successful submission of the project, not only will you be awarded a capstone certificate but you will have a project that can be showcased to potential employers as a testament to your learning.
- Project 1: Fare Prediction for Uber
Domain: Delivery (Commerce)
Uber, one of the largest US-based taxi providers, wants to improve the accuracy of fare predicted for any of the trips. Help Uber by building and choosing the right model.
- Project 2: Test bench time reduction for Mercedes-Benz
Mercedes-Benz, a global Germany-based automobile manufacturer, wants to reduce the time it spends on the test bench for any car. Faster testing will reduce the time to hit the market. Build and optimize the algorithm by performing dimensionality reduction and various techniques including xgboost to achieve the said objective.
- Project 3: Products rating prediction for Amazon
Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews on other similar products. Amazon would like to improve this recommendation engine by predicting ratings for the non-rated products and add them to recommendations accordingly.
- Project 4: Demand Forecasting for Walmart
Predict accurate sales for 45 stores of Walmart, one of the leading US-based leading retail stores, considering the impact of promotional markdown events. Check if macroeconomic factors like CPI, unemployment rate, etc. have an impact on sales.
- Project 5: Improving customer experience for Comcast
Comcast, one of the leading US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction if any. The company is also looking for key recommendations that can be implemented to deliver the best customer experience.
- Project 6: Attrition Analysis for IBM
Domain: Workforce Analytics
IBM, one of the leading US-based IT companies, would like to identify the factors that influence the attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.
- Project 7: NYC 311 Service Request Analysis
Perform a service request data analysis of New York City 311 calls. You will focus on data wrangling techniques to understand patterns in the data and visualize the major complaint types.
- Project 8: MovieLens Dataset Analysis
The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in several research projects in the fields of information filtering, collaborative filtering, and recommender systems. Here, we ask you to perform an analysis using the Exploratory Data Analysis technique for user datasets.
- Project 9: Stock Market Data Analysis
Domain: Stock Market
As a part of this project, you will import data using Yahoo data reader from the following companies: Yahoo, Apple, Amazon, Microsoft, and Google. You will perform fundamental analytics, including plotting, closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all of the stocks.
Who Should Enrol
With the demand for AI in a broad range of industries, Simplilearn’s AI course is well suited for a variety of roles and disciplines, including:
- Developers aspiring to be an Artificial Intelligence Engineer or Machine Learning Engineer
- Analytics Managers who are leading a team of analysts
- Information Architects who want to gain expertise in Artificial Intelligence algorithms
- Analytics professionals who want to work in machine learning or artificial intelligence
- Graduates looking to build a career in Artificial Intelligence and machine learning
- Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight
Participants in this course should have:
- An understanding of the fundamentals of Python programming
- Basic knowledge of statistics
- 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 – Advanced Deep Learning and Computer Vision
- Course 6 – Natural Language Processing (NLP)
- Course 7 – AI Capstone Project
IBM Watson for Chatbots
This course provides a practical introduction on how to build a chatbot with Watson Assistant without writing any code and then deploy your chatbot to a real website in less than five minutes. It will teach you to plan, build, test, analyze, and use your first chatbot.
Accelerated Deep Learning with GPU
In this Accelerated Deep Learning course with GPU by IBM, you will learn how to use accelerated hardware to overcome the scalability problem in Deep Learning. The course will begin with a quick review of Deep Learning, how to accelerate a Deep Learning model. It will then progress to Deep Learning in the Cloud and distributed Deep Learning.
Machine Learning with R
In this course, you will learn how to write R code, learn about R’s data structures, and create your own functions. With the knowledge gained, you will be ready to undertake your first very own data analysis. You’ll further learn about Supervised versus Unsupervised Learning, look into how Statistical Modeling relates to Machine
Access Period of Course
1 year from date of enrolment
The awesome learning experience with Simplilearn. I am in the Artificial Intelligence Engineer Master’s Program. So far, I have completed up to the Data Science with Python course. 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.
I would give a 5-star rating for the Simplilearn course I took. It helps me understand the content easily through online self-learning videos, and trainers assist us with their enriched knowledge, as well.
I took the AI Master’s 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.
- Students 0 student
- Max Students1000
- Duration211 hour
- Skill levelall
- Re-take course1000
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 - Advanced Deep Learning and Computer Vision
Advanced Deep Learning and Computer Vision
Course 6 - Natural Language Processing (NLP)
The Natural Language Processing course gives you a detailed look at the science of applying machine learning algorithms to process large amounts of natural language data. NLP is driving the growth of the AI market, and this course helps you develop the skills required to become an NLP Engineer.
Course 7 - AI Capstone Project
Simplilearn’s Artificial Intelligence (AI) Capstone project will give you an opportunity to implement the skills you learned in the masters of AI. With dedicated mentoring sessions, you’ll know how to solve a real industry-aligned problem. The project is the final step in the learning path and will help you to showcase your expertise to employers.