Artificial intelligence (AI) and AI engineering have been witnessing significant growth, and numerous statistical indicators support the attractiveness of becoming an AI engineer.
According to the World Economic Forum, the demand for AI and machine learning specialists is expected to increase by 60% by 2025.
In the U.S., the Bureau of Labor Statistics projected a 15% growth in employment for computer and information research scientists (which includes AI engineers) from 2019 to 2029, much faster than the average for all occupations.
AI engineers typically command higher-than-average salaries due to their specialized skill set and high demand. In the U.S., according to Glassdoor, the average base pay for AI engineers exceeded $100,000 per year, and senior AI engineers often earned considerably more.
Numerous industries have been embracing AI technologies. This adoption spans sectors like healthcare, finance, automotive, retail, and more, signifying many opportunities for AI engineers to apply their skills across various domains.
The Global Generative AI market has huge potential with the current market trends. It is expected to grow to $667.9 billion by 2030.
You will obtain certificates from IBM and Simplilearn upon completing these courses. These certificates will attest to your abilities as an expert in AI. In addition, you will receive the following:
Masterclass by IBM experts
Ask-Me-Anything sessions with IBM leadership
Hackathons conducted by IBM
IBM Certificates for IBM courses
Industry-recognized Program completion certificate from Simplilearn
You will be able to help you find a dream career after completing the AI Masters Program in collaboration with IBM. AI-certified experts are well-suited for the following positions:
Our committed team is here to assist you through email, chat, calls, and community forums. On-demand support is available to guide you through masters in artificial intelligence. Once you finish masters in ai, you will gain lifelong access to our community forum.
Delve into AI basics and generative AI principles. Grasp the importance of explainable AI. Employ prompt engineering to enhance generative AI performance. Understand ChatGPT's mechanisms, features, and constraints. Explore varied ChatGPT applications. Gain foresight into generative AI's future and challenges.
Discover procedural and object-oriented programming. Uncover Python's benefits. Set up Python and its IDE. Master Jupyter Notebook. Apply Python basics like identifiers, indentation, and comments. Understand data types, operators, and string functions. Explore Python loops and variable scopes. Learn about OOP, its features, and elements like methods, attributes, and access modifiers.
Kickstart your learning of Python for Data Science with this Data Scientist course and familiarize yourself with programming, tastefully crafted by IBM.
* Gain career success with our comprehensive Machine Learning course
* Learn from 40+ hrs of Applied Learning and interactive labs
* Complete 4 hands-on projects to solidify your understanding
* Receive mentoring support throughout your learning journey
* Master essential machine learning concepts for certification
* Gain the skills needed to become a successful machine learning engineer
Differentiate deep learning from machine learning. Explore various neural network types. Excel at forward and backward propagation in deep neural networks. Introduce modeling and performance enhancement in deep learning. Understand hyperparameter tuning and model interpretability. Learn dropout and early stopping implementation. Master CNNs, object detection, and RNN fundamentals. Grasp PyTorch basics and neural network creation.
The capstone project allows you to implement the skills you learned throughout this bootcamp. You will solve industry-specific challenges by leveraging various AI and ML techniques. The capstone project will help you showcase your expertise to employers.
Our Masters in Artificial Intelligence is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.
The knowledge and AI skills you've gained working on projects, simulations, and case studies will set you ahead of the competition.
Talk about your AI masters certificate on LinkedIn, Twitter, and Facebook, boost your resume, or frame it - tell your friends and colleagues about it.
A Master’s in Artificial Intelligence helps you gain a competitive edge over your peers and build job-ready skills. The instruction is offered by top-notch industry experts who have rich domain experience. By enrolling in this AI master's program, you will clearly understand various AI concepts like machine learning, natural language processing, computer vision, deep learning, neural networks, etc.
No, knowledge of coding is not mandatory for taking up this master's in artificial intelligence. It would, however, be beneficial to grasp the concepts faster.
A Master in Artificial Intelligence is a rigorous training program that helps students learn about this powerful technology from scratch and develop work-ready AI skills.
Professionals with a thorough knowledge of AI ideas have many opportunities. They can apply for AI Specialist, Machine Learning Engineer, NLP Scientist, AI Research Analyst, and Data Scientist.
You will be entitled to acquire the Masters in AI certificate, which will attest to your AI engineer abilities, provided you meet the following minimum requirements.
Course | Course completion certificate | Criteria |
Introduction to Artificial Intelligence Course |
Required | 85% of Online Self-paced completion and Pass Assessment test at 80% |
Data Science with Python | Required | 85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, a score above 75% in course-end assessment, and successful evaluation in at least 1 project |
Machine Learning | Required | 85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom and successful evaluation in at least 1 project |
Deep Learning with Keras and TensorFlow |
Required | Attend 1 Live Virtual Classroom and successful evaluation in at least 1 project and score 70% for course-end assessment. |
Advanced Deep Learning and Computer Vision | Required | Attend 1 LVC batch, Pass a Project, Pass an Assessment test 70% |
AI Capstone Project | Required | Attendance of 1 Live Virtual Classroom and successful completion of the capstone project |
Math principles such as statistics, probability, linear algebra, calculus, and Bayesian algorithms should be understood by professionals who want to start AI careers. Statistics, learning theory, problem-solving, classical mechanics, and language processing are all skills they'll need. It is also suggested that you know at least one programming language, data structure, and logic.