7 tips to choose an AI course and top options to consider
Artificial intelligence (AI) is one of the latest tech advancements that is believed to have the potential to shape the future. This is why, many workplaces are seeking candidates well-versed in AI tech and tools. Fortunately, anyone can learn about AI with hundreds of online and offline courses being offered by renowned universities, online platforms, and tech experts today. That said, choosing the right one is important for getting the career opportunities one wants.
Tips to choose the right AI courses
1. Establish the objective
The first step is understanding why one wants to join an AI course. Whether it is to explore new technologies, lead an AI-driven startup, acquire more technical skills, switch careers, or apply AI to current business practices, the reason should dictate the type of course one chooses. This is because the right course content will vary based on specific needs. For example, aspiring AI researchers, machine learning engineers, and developers may all study similar introductions and fundamentals of the field, but the desired specialization, projects, and applications of AI will be completely different. So, the choice of course should be based on the kind of knowledge and skills one wants to develop.
2. Assess existing knowledge level
AI courses can have varying levels of difficulty to cater to specific learners. Some courses may only touch upon the basics and theoretical knowledge, while some may dive deep into the real-world application of the technology. Additionally, some may offer hands-on projects and practice exercises for those already familiar with the technology. So, before choosing a course, one must decide if their current understanding of AI is at beginner, intermediate, or advanced level. Then, one can find a corresponding course. For instance, if new to the subject, one can find a beginner course focusing on basics like programming languages, deep learning, machine learning, and other topics under AI.
3. Check course requirements
Some courses also require candidates to have a basic qualification, such as a bachelor’s degree in computer science or engineering. Alternatively, they may need participants with extensive knowledge of mathematics, statistics, or programming to study AI. So, to avoid rejections, one should ensure that one meets the criteria before applying.
4. Research and compare courses
Ideally, one should look up a few key details for all courses before finalizing the best option.
Course content: This refers to the kind of topics a course will cover. From machine learning algorithms, neural networks, and data preprocessing to practical applications of AI in various fields, the content varies from one course to another. Even for beginners, it is best to take up a course that covers the practical applications of AI technology. Understanding the real-world uses of AI can help one understand the concept better.
Instructor profiles: Staff or faculty members who will conduct the course should ideally be industry experts or those with considerable experience in using AI. So, one should check the instructor’s details, like their credentials, and then choose a course that seems to have experienced instructors.
5. Consider the format
It is also important to shortlist and compare different courses in terms of their offerings and how they will be conducted. Some courses may be entirely online, allowing one to study at their own pace at any time, while others may be in-person or hybrid. All formats have their pros and cons. For instance, online courses are ideal for busy students or working professionals but may not provide live instruction or an opportunity to interact with other participants. So, one should assess their requirements and choose the best course format for them.
6. Read testimonials
It is best to go through the reviews of a particular course online before signing up for it. This step helps one see what others have to say about the course. Often, the most genuine testimonials will discuss both pros and cons of a particular course, like availability or lack of instructor support, content quality, or whether it provides certification.
7. Check for certification
Almost all courses provide a certificate to those who successfully complete the course, but it’s best to confirm this detail. Additionally, one should check if the certification is valued and recognized in the industry. This will boost the chances of getting better job opportunities.
Popular AI courses to consider
With a single online search, one will find many AI courses today. That said, AI is a vast and rapidly advancing field, so it’s important to choose courses that are up-to-date and popular.
Beginners can start with
– Introduction to Artificial Intelligence (AI) by IBM
– Microsoft Certified: Azure AI Engineer Associate
– Introduction to Generative AI by Google
– Stanford University Graduate Certificate in Artificial Intelligence
Intermediate and expert learners can explore
– Python for Data Science, AI & Development by IBM
– Google Cloud Professional Data Engineer
– AI for Business by the University of Pennsylvania
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