Building a Career in AI: From Student to Professional

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AI is a hot topic these days. It is being applied in all domains to solve real-life problems. Let’s discuss the steps for building a career in AI. 

 

Step 1: Build an Educational Foundation

 
Choose the degree that matches your career plans in AI. You can opt to get a degree in computer science, math or engineering. You’ll learn about coding languages and algorithms if you pursue a computer science course. Math and statistics courses include topics like probability, linear algebra and calculus. Engineering degrees usually focus on signal processing and robotics. There are several online courses available on different areas of AI. The courses include subsections that have  tutorials and assignments. They can be self-paced or have a fixed timeline. They can be found on popular platforms like edX, Coursera and Udemy. 

 

Step 2: Hands-on Learning

 

Engage in Projects and Competitions

Projects and competitions provide hands-on experience to solve real life problems using AI. They enhance our AI concepts and sharpen our problem-solving skills. You should first implement basic projects and then participate in challenges. Some common AI projects include image classification tasks like digit recognition or object detection. Natural language processing projects often involve sentiment analysis or chatbots. Some of the popular AI competitions are ImageNet Large Scale Visual Recognition Challenge (ILSVRC), AI for Social Good Challenge and NeurIPS Challenges. You should also participate in hackathons to explore different projects. 

 

Secure Internship Opportunities

An internship gives you practical experience and can also lead to a full-time job. Here’s how you can get one: Firstly, identify the artificial intelligence firms that involve interns Get connected to AI professionals online and offline. Ensure that your resume includes AI-related information in your skills section and educational background. Create a portfolio of AI projects and research. Make sure that you tailor your application to match the company and the position. It is essential to discuss the projects and experiences related to the internship role in the interview. Last but not the least,  don’t forget to contact the recruiters. 

 

Step 3: Build Portfolio and Network

 
A strong portfolio is important to show your skills in AI. The portfolio should be made in a professional manner. You should publish your work in academic journals and websites. Additionally, you should write articles and contribute to open-source projects. For example,  you can use GitHub to share your code and collaborate with peers. Networking leads to professional growth and knowledge exchange in the field of AI. Interact with experts on LinkedIn to stay connected within the AI community. Follow tech influencers such as Elon Musk and Andrew Nj and participate in their discussions. Attend local AI meetups to stay abreast of the latest AI trends. Moreover, join forums like Reddit’s r/MachineLearning and discuss AI topics. 

 

Step 4: Prepare for the Job Market

 

Craft a Resume and Cover Letter

You should ensure that the format of your resume is correct. Therefore, revise the given resume before submitting it to the job applications. You should change each cover letter to the job for which you are applying. The best way is to review the company’s culture to conform to their key requirements. You should explain in the cover letter why you are interested in the position. The content of the cover letter should be a brief summary of your best and related experience. 

 

Research Companies and Roles

You should study the employer and job position you are interested in beforehand. Get an idea about the company’s objective and recent happenings. You should also study the company’s culture and values. This will help you get an overall idea of how the company functions. It will also help you to answer interview questions.

Here are the AI careers that are popular at the moment: 

1. Data Scientist: Analyze data to find valuable insights and patterns
2. Machine Learning Engineer: Create and implement systems that use machine learning 
3. AI Research Scientist: Conduct research to develop new and improved AI technologies

 

Practice Interview Techniques

Business behavioral interview questions are often general and are not related to any profession. You could use the Structure, Task, Action, Result technique to answer these questions. The MIT Career Advising and Professional Development department has explained the STAR method in the form of a storytelling process.

 

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Mock interviews should be conducted to mimic the interview and get feedback regarding the performance. Moreover, you should do more coding problems on platforms like Leetcode.

 

Wrapping Up

 
You can have a successful career in AI by following the steps in this article. Each step is equally important in the order it is listed. If you acquire the necessary skills for AI, then you are ready to be a part of the world of AI. 
 
 

Jayita Gulati is a machine learning enthusiast and technical writer driven by her passion for building machine learning models. She holds a Master’s degree in Computer Science from the University of Liverpool.

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