The era of AI work has arrived! We are seeing a significant increase Hiring AI-related skills in the IT field and technology companies. Today, companies are hiring more AI/ML engineers than ever before.
Companies are increasingly focused on digital transformation and are looking for talent with AI-related skills. Roles such as AI trainer, NLP engineer, AI business strategist, and chief AI officer (CAIO) are on the rise. Not to mention the high salaries companies are paying to attract top talent to these roles. According to Glassdoor, the average salary for an AI/ML engineer in the US is $156,691.
Additionally, AI is a very dynamic field, and keeping up with new technologies is essential to growth. Whether you’re a newbie or a seasoned AI professional, continuous learning is key to advancing your career. AI careers are no different in this regard.
This article describes AI certifications that can help you build a strong skillset and succeed in your AI career.
The best AI certifications to advance your career
There are many AI certifications available online and offline. But which one is best for you? It can take time to find one that fits your skill level, aspirations, and budget. So we’ve done the hard work for you. We’ve listed some of the most popular AI certifications below to help you consider your next learning goal and get started.
Whether you’re a newbie looking to learn from scratch and break into the industry, take your skills to a new level, or move into an entirely new AI role, the certifications below can help.
1. IBM AI Developer Professional Certification by Coursera
level: Beginner (can be taken by both technical and non-technical subjects)
interval:10 course series (6 months, 4 hours a week)
Fee: free
Course outline:
This certification covers the fundamentals of applied AI, including: Machine learning, deep learning, neural networks. This course provides the fundamentals plus hands-on experience building virtual assistants, chatbots, and other AI applications using IBM Watson AI services and APIs. This course also covers Python. By working on real-world projects, you can develop advanced skills such as computer vision and machine learning.
Target skills:
- Python (for both data science and AI)
- Build AI applications using IBM Watson and its APIs
- Building a chatbot
- Introduction to computer vision and its applications
2. Essentials of Artificial Intelligence and Machine Learning at UPenn, Python Specialization with Coursera
level: Intermediate (Python programming experience required)
interval:4 months (8 hours a week)
Fee: free
Course outline:
UPenn’s Intermediate course is a comprehensive course to start learning AI and machine learning. This course builds a strong foundation for learners to start a career in AI from the history of artificial intelligence and training in deep learning models.
Target skills:
- python
- probability and statistics
- Search algorithms – *search, depth-first search, breadth-first search, etc.
- Deep learning models – perceptrons, neural networks, backpropagation
3. Artificial Intelligence Graduation Certificate by Stanford Institute of Technology
level: Intermediate (programming skills required)
interval: 20 course series (instructor-led courses)
Fee: $19,682 – $24,224
Course outline:
The program has a total of 20 courses, divided into 2 required courses and 18 elective courses. You must complete one of two required courses and choose one of 18 elective courses. You must have a GPA of 3.0 or higher in each course to move forward and earn your certification.
Target skills:
- In the required courses, you will learn:
- Supervised vs. unsupervised learning
- learning theory
- Reinforcement learning and control
There are many elective courses to choose from, including robotics, deep learning, and more.
4. MIT’s Professional Certification Program in Machine Learning and Artificial Intelligence
level: Advanced (requires at least 3 years of professional experience in a technical field)
interval:maximum. 3 years after taking the qualification course
Fee: The application fee is $325. Once you enroll in the program, you will be required to pay for each course separately as you attend.
Course outline:
This is an in-person program at MIT where you can develop advanced skills in machine learning and AI. This program is equally suitable for learners who want to hone their basic skills and advanced learners. This is because in order to complete the program, you must first take the prerequisite courses and then the advanced courses. To earn your certificate, you must complete 16 qualifying courses.
Target skills:
- big data
- text processing
- predictive modeling
5. Artificial Intelligence at UC Berkeley: Business Strategy and Applications
level: advanced
interval:2 months (4-6 hours a week)
Fee: $2625
Course outline:
This course focuses on building and developing AI strategy insights from a business perspective. This course delves into the application of AI in various aspects of business, including supply chain, automation, and personalizing the customer experience. By the end of the course, you will have built a project focused on implementing AI projects across your organization. This course covers natural language processing, robotics, computer vision, neural networks, and more.
Target skills:
- Artificial intelligence and its applications
- Organize and manage successful artificial intelligence application projects
- Leverage generative AI models and simulations for predictions
6. Deep Learning Specialization by Andrew Ng
level: Intermediate (requires Python programming experience, for loops, an understanding of data structures, and a basic understanding of linear algebra and ML)
interval:3 months (10 hours a week)
Fee: free
Course outline:
Our 5-course foundational course prepares you to develop AI technologies. Learn about deep learning by building and training neural networks using tools like TensorFlow and Hugging Face. By the end of the course, you will build a convolutional neural network.
Target skills:
- convolutional neural network
- LSTM
- Recurrent Neural Network
- transformers
- Strategies to improve neural network architectures such as Dropout, BatchNorm, and Xavier m /He initialization.
- TensorFlow
7. Overview of TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
level: Intermediate (Python coding experience required)
interval:22 hours
Fee: free
Course outline:
This course focuses on enabling learners to use TensorFlow internally and externally. Learn how to build, train, and optimize neural networks using TensorFlow.
Target skills:
- TensorFlow
- neural network
- Build, train, and improve neural networks
8. ARTiBA Artificial Intelligence Engineer
level: Intermediate (programming skills required)
interval: 180 days from the date of exam registration.
Fee: $550
Course outline:
This comprehensive certification validates the knowledge and skills you need to start a career in AI development. This course will help you develop expertise in AI and ML methodologies. Learn the basics of AI and ML, natural language processing, neural networks, and deep learning. By the time you complete the course, you will be able to conceive, build, train, and run machine learning models with confidence.
Target skills:
- supervised learning
- unsupervised learning
- ensemble learning
- Heuristic search method
- Build games with AI
- Probabilistic inference for continuous data
- Object detection and tracking
9. Google Cloud Generative AI Overview
level: entry level
interval:1 hour
Fee: free
Course outline:
Google’s introductory course explains what Generative AI is and how it differs from traditional machine learning models. Learn how to develop your own Gen AI apps using Google tools.
Target skills:
- What is generative AI?
- Generative AI model
- Building generative AI applications
10. Certified Artificial Intelligence Scientist (CAIS)TM) by the American Institute for Artificial Intelligence
level: forward
interval: 4-25 weeks (8-10 hours per week)
Fee: $894
Course outline:
This certification validates the ability of senior AI professionals and business leaders to create AI strategies and solutions that transform their businesses. Learn about strategic growth and product management while mastering the essentials of AI. This course also includes lessons on generative AI, engineering management, and computer vision.
Target skills:
- Fundamentals of AI and Machine Learning
- Deep learning and generative AI
- Strategic growth and product management
- Generation AI
- computer vision
- deep learning
conclusion
Artificial intelligence is changing the face of every industry with its applications. Earning a Professional AI certification will give you the skills you need to adapt and succeed in changing situations. Whether you need to improve your artificial intelligence skills or embark on an entirely new career path, certifications can help. So, register for your certification today!
related: How to Become a Business Intelligence Analyst: 5 Key Skills to Master
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