7 tips for choosing the right AI course for career growth

Artificial Intelligence (AI) impacts various industries, including IT, healthcare, finance, and manufacturing. Given the technology’s transformative potential, the demand for AI specialists has also skyrocketed in recent years. One way to enhance AI-related skills is to explore courses and certifications offered by renowned institutes and IT giants. These educational opportunities boost one’s portfolio, help one gain practical knowledge of these up-and-coming tools, and help one stay relevant and competitive in one’s industry.

Tips to choose the right AI courses

1. Define the learning objective
Determining the skills one wishes to learn is an important factor to consider. AI applications and their uses vary widely across different careers, so one should first understand the exact objectives of learning AI. The course can differ for data scientists, machine learning engineers, developers, and AI researchers.

2. Evaluate current knowledge
The course should advance one’s skill set. So, the first step is to check whether one is a beginner, intermediate, or advanced learner of AI and choose a suitable course that aligns with one’s needs. For example, beginners can take introduction to AI courses or choose a curriculum that covers the basics, theoretical concepts, and foundational skills, while advanced learners can take on hands-on projects, practice exercises, and specialized topics to improve their expertise.

3. Research institutions and courses
Next, thoroughly research which reputable institutions, online platforms, and universities offer comprehensive courses. Some key factors to consider include:

Course content
This can give a detailed idea about what topics the course will cover, including case studies and projects. One should also look for practical projects in the course to deepen one’s knowledge and ensure that one can effectively put the information to actual, real-world use.
Faculty members
Do not be swayed by the marketing and course highlights; thoroughly evaluate the instructor’s credentials and background. Learning from industry experts with experience in a specific field holds more value.
Delivery method
Both online and offline course delivery methods have pros and cons. Online courses are more flexible and suitable for working professionals, but they may not provide hands-on instructor review and interaction as the offline ones can.

4. Read previous students’ reviews
These are testaments to a course’s effectiveness, quality, and teaching style. Reviews help determine if the course meets students’ needs. They may often highlight the courses’ drawbacks, like insufficient instructor support, which can help prospective learners make better choices.

5. Check for any prerequisites
Some AI-based courses require candidates to have a deep and, often, academic understanding of mathematics, programming, and other subjects. Ensure one’s skilled in these areas and join any preparatory courses if needed to be eligible for the desired AI course.

6. Cost and certification
It’s important to select a course that offers a recognizable and credible certificate of completion, which is actually useful in the job market. Additionally, the cost of courses varies greatly depending on faculty, course duration, what it offers, and other factors.

7. Search for popular and best AI courses
There are several trending and popular AI courses focusing on different aspects of the technology. Deep learning courses cover topics like neural networks and computer vision, while machine learning courses focus on supervised and unsupervised learning. Additionally, there are courses on model monitoring and deployment of AI in real-world applications. Owing to the technology’s vast and rapidly advancing nature, it’s important to stay updated with the latest developments and join a course after thorough research.

Some popular courses with great market value include: