Not having artificial intelligence (AI) as an arsenal in your career toolkit is non-negotiable. AI advancements have drastically shaped multiple industries. From generating automated conversations to understanding human behavior, this technology helps achieve greater business value in the AI economy.
In a recent press release, Accenture announced the launch of Accenture LearnVantage to ensure its clients learn the latest technology skills in data and AI. These training services will help leaders across different industries bridge the gap these businesses lack. The services include industry-specific training and personalized learning experiences for technical and business users (C-suite members, business leaders in AI, data science, cloud and cyber security).
In this article, we will list down some of the best AI certifications to elevate your skills and career.
10 Top AI Certifications for Advancing Your Tech Career
People with AI skills can grab a whopping 47% salary raise. Whether you’re a beginner or a working professional, the below list of AI certifications is a hot commodity.
1. Coursera – Introduction to TensorFlow for AI, Machine Learning and Deep Learning
This certification is a four-course deep-learning program. This AI certification is one of the four-course series of the DeepLearning.AI TensorFlow Developer Professional Certificate.
What It Covers
It is a 22-hour program, and the course covers the following topics.
- Best practices for using TensorFlow
- Open-source machine learning framework
- Creating a basic neural network in TensorFlow
- Usage of convolutions to improve neural networks
- Training neural networks for computer vision applications
Prerequisites
This certification program is ideal for software developers looking to build AI-powered algorithms. Skills in Python coding are a must-have. Understanding deep learning and machine learning is helpful; however, not mandatory.
2. Udemy- Reinforcement Learning in Python
This course will help candidates learn the latest groundbreaking technologies like ChatGPT and GPT-4.
What It Covers
It is a 14.5-hour program and is ideal for candidates looking to learn the latest AI techniques.
- Relationship between reinforcement learning and psychology
- Reinforcement learning at the technical level
- How to apply gradient-based supervised machine learning methods
- Foundation for ChatGPT and GPT-4
- Implementing 17 different reinforcement learning algorithms
Prerequisites
This course is ideal for students and working professionals. Prior to registering for the course, the candidate needs to ensure they have the following prerequisites:
- Probability
- Calculus
- Linear Regression
- Object-Oriented Programming
- Python Coding [if/else, lists, loops, sets, dicts]
- Numpy Coding [matrix and vector operations]
3. edX – Computer Science for AI
This AI certification helps build a stronger foundation in programming skills mandatory for AI. By the end of this program, candidates can start designing intelligent systems at their own pace.
What It Covers
It is self-paced, and the approximate time to complete the course is 5 months.
- Usage of AI in Python programs
- Machine learning, Reinforcement learning and AI principles
- Graph search algorithms
- Designing intelligent systems
Prerequisites
Ideal for beginners and candidates looking to learn AI-related programming. However, a basic understanding of computer programming concepts is an add-on.
4. Coursera – IBM AI Engineering Professional Certificate
IBM AI engineering professional certificate is a 10-course series offered by IBM. This course will enable candidates to elevate their knowledge and skills required to start their career in AI engineering.
What It Covers
The approximate time to complete this course is six months, provided the candidate spends four hours on a weekly basis.
- Deploy AI applications using Python and Flask
- Building generative AI-powered apps and chatbots
- Fundamental concepts, building blocks and AI applications
Prerequisites
This certification course is an advanced program ideal for AI and ML engineers.
5. Coursera – CertNexus CAIP Professional Certificate
The CertNexus Certified Artificial Intelligence Practitioner (CAIP) Professional Certificate provides skills such as support vector machine (SVM), AI ethics, ML algorithms, artificial neural networks, data structures, and process management.
What It Covers
The recommended timeline to complete this certification course is approximately two months, provided the candidates devote at least 10 hours on a weekly basis.
- Learning specific AI and ML techniques to solve business problems
- Data analysis and model training
- Advanced AI algorithms in ML and deep learning
- Building multiple models within a workflow
- ML algorithms to solve common supervised and unsupervised learning problems [regression, classification and clustering]
Prerequisites
Ideal for data science professionals seeking to enhance careers in the AI field.
6. US AI Institute – Certified Artificial Intelligence Scientist [CAIS]
The CAIS certification is a strategic-level program that can help candidates looking to advance their careers in the leadership team and AI-led organizational transformation.
What It Covers
It is self-paced and might take approximately 4 to 25 weeks to complete.
- Developing suitable AI solutions
- Comprehensive AI strategies to solve business problems
Prerequisites
Ideal for professionals with 5+ years of experience in any engineering discipline.
7. MIT – Professional Certificate Program in Machine Learning & Artificial Intelligence
This certificate program guides professionals seeking skills in advanced AI technologies like predictive analytics, natural language processing, algorithmic methods and deep learning.
What It Covers
The program takes approximately 36 months to complete.
- Applying AI and machine learning concepts to data analytics
- Machine learning concepts
- AI best practices
Prerequisites
- Ideal for candidates having at least three years of working experience in a technical field or a bachelor’s degree in computer science, physics, statistics, and electrical engineering.
- Candidates whose work collides with data analysis and are looking to expand their skills by learning key concepts, ML and deep learning, AI algorithms, and formulation.
- Professionals looking for in-depth expertise and hands-on experience with the faculty at MIT, and industry experts.
8. Coursera – Generative AI for Everyone
The GenAI certification course helps candidates understand how GenAI impacts businesses, along with strategies and approaches to solve problems. Candidates enrolled for this course can directly learn from experts like Andrew NG.
What It Covers
Candidates enrolled in this program can easily complete the course within an hour. It is a foundational course that covers the basics, applications and ethical considerations of GenAI.
- GenAI capabilities and limitations
- Broad applications of GenAI
- GenAI examples and practical application
Prerequisites
This course is non-technical and is available for everyone interested in GenAI.
9. Udemy – Build an AI with ChatGPT-4
This course enables candidates to build different AIs using models like Q-learning, deep Q-learning, deep convolutional Q-learning, A3C (Asynchronous Advantage Actor-Critic, SAC (Soft Actor-Critic), pre-trained LLMs, and PPO (Proximal Policy Optimization).
What It Covers
The total length of this course is approximately 15 hours and 9 minutes and includes an on-demand video, 17 articles and 10 downloadable resources.
- Fine-tuning LLMs with knowledge augmentation
- Strategies and genetic algorithms
- Solving real-world problems using AI
- Building seven different AI’s for different applications
Prerequisites
Candidates with Python knowledge can enroll in this course.
10. UC Berkeley – AI For Executive Program
The AI for Executive program course is exclusively curated for executives looking to get trained for leadership roles. Driven by the Berkeley Haas faculty and industry experts, this program can help you learn the process of evaluating AI systems, strategies for AI adoption and its potential impact.
What It Covers
It is a three-day course and candidates enrolled in this program need to be available in person.
- Hands-on AI and strategy exercises
- Leading-edge curriculum
- Access to the AI alumni community
- Networking and building connections with the faculty and industry experts
Prerequisites
The AI executive program is ideal for:
- Engineers and other technical roles seeking to enhance their skills in AI
- Professionals seeking to stay in sync with the current AI trends
- Senior executive seeking to establish AI strategies for their organization
- Senior-level managers responsible for managing AI for the team and department
In Conclusion
AI is already transforming the way people work across multiple industries. People with AI skills are in high demand, and even organizations are willing to pay a premium for such candidates. A 2023 study by AWS reveals information that mentions a 43% raise for candidates in sales and marketing, while 47% raise for IT professionals, and a 42% raise for those in the finance industry.
With the rapid rise in GenAI, many growing clients and customers are in dire need of upskilling their workers in AI, cloud and data.
In this article, we’ve covered the basic and advanced AI certifications course to choose from. Looking ahead, it is evident that employers expect candidates to have advanced AI knowledge and skills when hiring.
