Practice these common deep learning interview questions to help you prepare for a job interview as you pursue your career in deep learning and artificial intelligence.
Learning about the role of AI and deep learning in information technology, machine learning, or data science can help you prepare for a number of different roles and positions, including natural language processing scientist, business intelligence developer, computational linguist, machine learning engineer, software developer, and more.
As you think about your role in the developing artificial intelligence (AI) world, it’s helpful to consider what you bring to the field, including your experience, skill set, and problem-solving ability. To help you prepare for your next job interview, explore these common deep learning interview questions.
Deep learning, a subset of machine learning and a type of artificial intelligence is characterized by using neural networks to mimic how humans self-correct when it comes to thinking and learning. Deep learning AI involves using hidden layers within the neural network to identify and learn patterns to act more independently of its user. By detecting its own errors, a deep learning AI application can continuously learn from its own outputs and improve itself without the help of humans.
The following are some common deep learning interview questions you may encounter when applying for a job related to deep learning or another relevant field like data science, information technology, machine learning, or artificial intelligence. As you study each question, consider how you would answer it and why an interviewer would choose these topics for your particular role.
What they’re really asking: How much experience do you have with AI tools?
This question asks you to discuss your experience using AI-related tools in previous positions or schooling. Your interviewer is curious about your proficiency level with an assortment of AI tools that their company might use, so ensure you are discussing all levels of experience with any artificial intelligence software or programs you have encountered in the past.
To best answer this question, you can talk about the tools you are most familiar with and elaborate on any specific tools you use that the company also works with. It is a good idea to research what tools the company uses ahead of time to find common ground.
Other forms this question might take:
What AI tools do you prefer to use?
What is your proficiency level with AI tools?
What they’re really asking: What certifications do you have that qualify you for this position?
Asking about your certifications means your interviewer wants to know more about how you have expanded your knowledge and commitment to the field.
It’s best to answer honestly and describe all certifications or AI-related training to your interviewer to demonstrate your experience in deep learning. Discussing your certifications can make you a more competitive applicant for the position.
This is an opportunity to describe how the certifications you’ve earned have streamlined your processes, enhanced your quality of work, and can provide value to your new company.
Other forms this question might take:
What level of education or degree specializations do you have in deep learning?
Have you earned any specializations in the deep learning field?
What they’re really asking: Do you understand the foundations of this field?
By asking you to define deep learning, your interviewer may be checking your competency and understanding of the field and the term. They may want to know your definition of deep learning and how you respond to a question that could have a broad range of answers.
This question also asks you to break down a complicated topic into simpler terms, which could help show your understanding of deep learning and how you would communicate that understanding to clients and co-workers. Provide a concise answer that will demonstrate to your employer how adept you are at communicating complex topics in simple terms.
Other forms this question might take:
How would you describe deep learning to a nontechnical person?
In simple terms, what is deep learning?
What they’re really asking: Do you have experience working with deep learning in teams?
In this case, the interviewer wants to know more about your experience using different kinds of AI-related tools and in what context you have used them. They are curious to learn more about your responsibilities and competencies regarding applying your skills and how well-suited you are to leading projects.
To answer this question, consider your most impressive projects involving a wide range of AI and deep learning tools and extensive collaboration among team members. Demonstrating your work ethic and ability to complete projects can impress potential employers and give them a better understanding of your leadership skills.
Other forms this question might take:
What’s the most interesting project you’ve worked on?
What projects relevant to this position have you worked on?
What are some examples of projects you’ve done in the past?
What they’re really asking: What are your problem-solving strategies?
By asking you to identify a problem, your interviewer seeks to evaluate your critical thinking skills and ability to solve complex problems. They want to know how you deal with challenges and navigate difficult scenarios.
To answer this question, you can think about a time you had a problem and how you approached it. You should explain how you solved—or did not solve—a problem related to deep learning.
Other forms this question might take:
What’s an example of a problem you faced, and how did you solve it?
What is your method for problem-solving?
What they’re really asking: Are you familiar with the controversies surrounding deep learning?
Prompting you to delve into this topic means that your interviewer is curious about your stance on the transparency and abilities of deep learning AI and your media literacy surrounding AI-related controversies.
By asking you to consider the ethics of AI and deep learning, your interviewer can decipher whether you have researched this matter and how you feel about deep learning and its inability to mimic human intelligence and respond to interventions or changes precisely. You could answer this question by focusing on the issues of data privacy, accountability, bias, and verification problems related to AI.
Other forms this question might take:
What are the ethical implications of using deep learning software?
What is your personal stance on using deep learning?
What they’re really asking: Have you conducted research on our company’s approaches?
In this question, the interviewer is testing your background knowledge of the company and how your skills and experience align with its approach to using applications like AI, deep learning, and machine learning. They want to know why you are applying to their company in particular and if you have researched its use of deep learning.
When answering this question, make sure to emphasize certain points you have researched in addition to how your approaches would either align with or differ from the company's. Focus on what makes the company interesting to you, and be specific. Research the company by exploring its website, LinkedIn profile, social media pages, and related news reports.
Other forms this question might take:
What interests you about our company’s deep learning strategies?
Would you change anything about our company’s approach to deep learning?
What they’re really asking: Are you experienced with different deep learning frameworks?
If an interviewer asks you to discuss deep learning frameworks you’ve used in the past, discuss your experience to show them what frameworks you are comfortable with and if you have expertise in any of them.
You can detail your past experiences to demonstrate what kind of worker you are and how familiar you may be with different tools and applications. This is a good opportunity for you to expand on anything that might not be on your resume and impress the interviewer with your technical competencies.
Other forms this question might take:
What is your experience with deep learning frameworks?
What kinds of applications or frameworks have you worked with before?
What platforms for deep learning are you familiar with?
Besides some of the questions, an interviewer may ask you in a deep learning interview, here are several additional tips to help you prepare:
Research the company ahead of time.
Arrive to the interview well-versed in the organization’s mission and values with a prepared list of questions to ask them. If you can discuss essential details about the company, you can show yourself as a knowledgeable and educated candidate for the position. In addition, you can learn whether the company might be a good fit for you.
Learn about current software and stay up to date on deep learning advancements.
It’s important to prepare for personal questions, but you will also need to answer technical questions and perform tasks if required. It is normal for interviewers to ask you to code or apply deep learning frameworks, so you’ll want to be able to both answer and perform with up-to-date background knowledge.
Arrive well-informed on deep learning topics.
Interviewers may expect you to discuss deep learning topics like neural networks, transformers, multilayer perceptrons, system design, embeddings, and any new artificial intelligence applications using deep learning methods. By demonstrating that you are experienced and well-versed in the deep learning world, you can impress your interviewer and distinguish yourself as a competitive applicant.
When preparing for a deep learning interview, it’s essential to consider what experience and skills you have listed on your resume. Earning a relevant certificate can help you stand out among other applicants, especially in competitive AI and information technology fields. On Coursera, you can take courses like the Deep Learning Specialization, offered by DeepLearning.AI, where you’ll have the opportunity to learn how to build and train deep neural networks and master the fundamentals of deep learning.
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