Artificial Intelligence Engineer Masters Program
Learning Experience | 9.4 |
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Artificial Intelligence Engineer Masters Program gives concise training on the skills required to become a successful Artificial Intelligence Engineer.
Scope and Future of Artificial Intelligence (AI)
Before going in detail on Artificial Intelligence Engineer Masters Program, let’s first understand the scope of Artificial Intelligence. AI is going to boost medicine, insurance, healthcare, logistics, transportation, robotics, engineering, space, military activities, and marketing in a large way. Also, the future needs of organizations will be the smartest professionals with AI skills. Tech giants companies such as Amazon, Facebook, Uber, Intel, Samsung, IBM, Accenture, Google, Adobe, Microsoft, and others are the leading ones deploying Artificial Intelligence. There are lot of others around you, naturally tuned into the fact that as many as 31% of organizations around the world are likely to use AI in the current and upcoming years.
The current and future demand is staggering. The New York Times reports candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S for AI Engineers with the required skills.
About the Artificial Intelligence Engineer Masters program
This Artificial Intelligence Engineer Masters Program, in collaboration with IBM, gives concise training on the skills required to become a successful Artificial Intelligence Engineer. Throughout, this exclusive online course will let you gain mastery in Deep Learning, Machine Learning, and the programming languages required to excel in this domain and kick-start your career in Artificial Intelligence.
This course is developed in collaboration with IBM which is the second-largest Predictive Analytics and Machine Learning solutions provider globally. It is a joint partnership with Simplilearn in which IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. This course in collaboration with IBM will make students industry-ready for Artificial Intelligence and Data Science job roles.
Upon completion of this Data Scientist’s online Masters program, you will receive the certificates from IBM and Simplilearn in the Data Science courses on the learning path. These certificates will testify to your skills as an expert in Data Science. Along with you will also receive the following:
- USD 1200 worth of IBM cloud credits that you can leverage for hands-on exposure.
- Access to IBM cloud platforms featuring IBM Watson and other software for 24/7 practice.
- Industry-recognized Data Scientist Master’s certificate from Simplilearn.
What you will learn from this course
In this course you will cover the following points:
- You will learn about the major applications of Artificial Intelligence across various use cases across various fields like customer service, financial services, healthcare, etc.
- Learn to implement classical Artificial Intelligence techniques such as search algorithms, neural networks, and tracking.
- You will gain the ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques.
- Clearly, you will understand the concepts of Tensor Flow, its main functions, operations, and the execution pipeline.
- 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.
- You will 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.
- You will be able to 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.
- Able to 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).
Who Should Enroll in this Program?
With the high demand for Artificial Intelligence in a broad range of industries such as banking and finance, manufacturing, transport and logistics, healthcare, home maintenance, and customer service, the Artificial Intelligence Engineer Masters Program is well suited for a variety following profiles such as:
- Developers aspiring to be an ‘Artificial Intelligence Engineer’ or Machine Learning engineers.
- Analytics managers who are leading a team of analysts.
- Information architects who want to gain expertise in Artificial Intelligence algorithms.
- Graduates looking to build a career in Artificial Intelligence and Machine Learning.
Syllabus
There are seven courses in this Artificial Intelligence Engineer Masters program
1. Introduction to Artificial Intelligence
This course of Introduction to Artificial Intelligence (AI) is designed to assist learners to decode the mystery of artificial intelligence (AI) and its business applications. This AI for beginner’s course provides an overview of AI concepts and workflows, machine learning and deep learning, and performance metrics.
- Course Introduction.
- Decoding Artificial Intelligence and Fundamentals of Machine Learning and Deep Learning.
- Machine Learning Workflow and Performance Metrics.
(more on Introduction to AI)
2. Artificial Intelligence Engineer Masters: Data Science with Python
This Data Science with Python course will provide you 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.
- Overview of Data Science and Data Analytics.
- Statistical Analysis and Business Applications and Python Environment Setup and Essentials.
- Mathematical Computing with Python (NumPy).
- Scientific computing with Python (Scipy).
- Data Manipulation with Pandas.
- Machine Learning and Natural Language Processing with Scikit Learn.
- Data Visualization in Python using matplotlib.
- Web Scraping with BeautifulSoup.
- Python integration with Hadoop MapReduce and Spark.
(more on Data Science with Python)
3. Artificial Intelligence Engineer Masters: Machine Learning
In this program, you will be able to 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.
- Introduction to AI and Machine Learning.
- Data Preprocessing.
- Supervised Learning and Unsupervised Learning.
- Feature Engineering and Supervised Learning Classification.
- Time Series Modeling, Ensemble Learning, Recommender Systems, and Text Mining
(more on machine learning)
4. Artificial Intelligence Engineer Masters: 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. This course will let you gain mastery in deep learning concepts and models using Keras and TensorFlow frameworks and implement deep learning algorithms, preparing you for a career as Deep Learning Engineer.
- Introduction to Tensorflow.
- Convolutional Networks and Recurrent Neural Network.
- Restricted Boltzmann Machines (RBM) and Autoencoders.
(more on Deep Learning with Keras and TensorFlow)
5. Artificial Intelligence Engineer Masters: Advanced Deep Learning and Computer Vision
Advanced Deep Learning and Computer Vision
- 2 Image Classification with Keras and Construct a GAN with Keras.
- Object Detection with YOLO.
- Generating Images with Neural Style.
6. Artificial Intelligence Engineer Masters: Natural Language Processing
This course of 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. Natural Language Processing is driving the growth of the AI market, and this course helps you develop the skills required to become a Natural Language Processing Engineer.
- Processing Raw Text with NLTK.
- A Practical Real-World Example of Text Classification.
- Finding Useful Information from Piles of Text.
- Developing a Speech to Text Application Using Python.
(more on Natural Language Processing)
7. Artificial Intelligence Engineer Masters Capstone Project
This 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, also you will 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.
Project description:
The project is the final step in the learning path and will help you to showcase your expertise to employers.
This Artificial Intelligence Engineer Master’s 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.
Pre-requisites
Participants in the Artificial Intelligence Engineer Masters program should have an understanding of the fundamentals of Python programming and basic knowledge of statistics.
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Description
Scope and Future of Artificial Intelligence (AI)
Before going in detail on Artificial Intelligence Engineer Masters Program, let’s first understand the scope of Artificial Intelligence. AI is going to boost medicine, insurance, healthcare, logistics, transportation, robotics, engineering, space, military activities, and marketing in a large way. Also, the future needs of organizations will be the smartest professionals with AI skills. Tech giants companies such as Amazon, Facebook, Uber, Intel, Samsung, IBM, Accenture, Google, Adobe, Microsoft, and others are the leading ones deploying Artificial Intelligence. There are lot of others around you, naturally tuned into the fact that as many as 31% of organizations around the world are likely to use AI in the current and upcoming years.
The current and future demand is staggering. The New York Times reports candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S for AI Engineers with the required skills.
About the Artificial Intelligence Engineer Masters program
This Artificial Intelligence Engineer Masters Program, in collaboration with IBM, gives concise training on the skills required to become a successful Artificial Intelligence Engineer. Throughout, this exclusive online course will let you gain mastery in Deep Learning, Machine Learning, and the programming languages required to excel in this domain and kick-start your career in Artificial Intelligence.
This course is developed in collaboration with IBM which is the second-largest Predictive Analytics and Machine Learning solutions provider globally. It is a joint partnership with Simplilearn in which IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. This course in collaboration with IBM will make students industry-ready for Artificial Intelligence and Data Science job roles.
Upon completion of this Data Scientist’s online Masters program, you will receive the certificates from IBM and Simplilearn in the Data Science courses on the learning path. These certificates will testify to your skills as an expert in Data Science. Along with you will also receive the following:
- USD 1200 worth of IBM cloud credits that you can leverage for hands-on exposure.
- Access to IBM cloud platforms featuring IBM Watson and other software for 24/7 practice.
- Industry-recognized Data Scientist Master’s certificate from Simplilearn.
What you will learn from this course
In this course you will cover the following points:
- You will learn about the major applications of Artificial Intelligence across various use cases across various fields like customer service, financial services, healthcare, etc.
- Learn to implement classical Artificial Intelligence techniques such as search algorithms, neural networks, and tracking.
- You will gain the ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques.
- Clearly, you will understand the concepts of Tensor Flow, its main functions, operations, and the execution pipeline.
- 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.
- You will 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.
- You will be able to 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.
- Able to 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).
Who Should Enroll in this Program?
With the high demand for Artificial Intelligence in a broad range of industries such as banking and finance, manufacturing, transport and logistics, healthcare, home maintenance, and customer service, the Artificial Intelligence Engineer Masters Program is well suited for a variety following profiles such as:
- Developers aspiring to be an ‘Artificial Intelligence Engineer’ or Machine Learning engineers.
- Analytics managers who are leading a team of analysts.
- Information architects who want to gain expertise in Artificial Intelligence algorithms.
- Graduates looking to build a career in Artificial Intelligence and Machine Learning.
Syllabus
There are seven courses in this Artificial Intelligence Engineer Masters program
1. Introduction to Artificial Intelligence
This course of Introduction to Artificial Intelligence (AI) is designed to assist learners to decode the mystery of artificial intelligence (AI) and its business applications. This AI for beginner’s course provides an overview of AI concepts and workflows, machine learning and deep learning, and performance metrics.
- Course Introduction.
- Decoding Artificial Intelligence and Fundamentals of Machine Learning and Deep Learning.
- Machine Learning Workflow and Performance Metrics.
(more on Introduction to AI)
2. Artificial Intelligence Engineer Masters: Data Science with Python
This Data Science with Python course will provide you 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.
- Overview of Data Science and Data Analytics.
- Statistical Analysis and Business Applications and Python Environment Setup and Essentials.
- Mathematical Computing with Python (NumPy).
- Scientific computing with Python (Scipy).
- Data Manipulation with Pandas.
- Machine Learning and Natural Language Processing with Scikit Learn.
- Data Visualization in Python using matplotlib.
- Web Scraping with BeautifulSoup.
- Python integration with Hadoop MapReduce and Spark.
(more on Data Science with Python)
3. Artificial Intelligence Engineer Masters: Machine Learning
In this program, you will be able to 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.
- Introduction to AI and Machine Learning.
- Data Preprocessing.
- Supervised Learning and Unsupervised Learning.
- Feature Engineering and Supervised Learning Classification.
- Time Series Modeling, Ensemble Learning, Recommender Systems, and Text Mining
(more on machine learning)
4. Artificial Intelligence Engineer Masters: 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. This course will let you gain mastery in deep learning concepts and models using Keras and TensorFlow frameworks and implement deep learning algorithms, preparing you for a career as Deep Learning Engineer.
- Introduction to Tensorflow.
- Convolutional Networks and Recurrent Neural Network.
- Restricted Boltzmann Machines (RBM) and Autoencoders.
(more on Deep Learning with Keras and TensorFlow)
5. Artificial Intelligence Engineer Masters: Advanced Deep Learning and Computer Vision
Advanced Deep Learning and Computer Vision
- 2 Image Classification with Keras and Construct a GAN with Keras.
- Object Detection with YOLO.
- Generating Images with Neural Style.
6. Artificial Intelligence Engineer Masters: Natural Language Processing
This course of 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. Natural Language Processing is driving the growth of the AI market, and this course helps you develop the skills required to become a Natural Language Processing Engineer.
- Processing Raw Text with NLTK.
- A Practical Real-World Example of Text Classification.
- Finding Useful Information from Piles of Text.
- Developing a Speech to Text Application Using Python.
(more on Natural Language Processing)
7. Artificial Intelligence Engineer Masters Capstone Project
This 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, also you will 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.
Project description:
The project is the final step in the learning path and will help you to showcase your expertise to employers.
This Artificial Intelligence Engineer Master’s 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.
Pre-requisites
Participants in the Artificial Intelligence Engineer Masters program should have an understanding of the fundamentals of Python programming and basic knowledge of statistics.
Note: Your review matters
If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.
FAQ
Specification:
- Simplilearn
- IBM
- Masters program
- Instructor-led
- Advanced
- Paid Course (Paid certificate)
- English
- Python R Scala
- Apache Spark
- Basic Maths Basic Scripting in Python Basic Scripting in R Fundamentals of calculus Linear Algebra Probability Basics Statistics Basics
- Artificial intelligence Data Science Data Science with 'Python' Deep learning Keras Machine learning Natural language processing TensorFlow
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