pranav kumar
how to get into product based companies in fields of ML ?
I am studying in a private engineering college in my native as im not good with hostles after my 12th even after getting decent score(91%). only service based mass companies like TCS, wipro, cognizant,etc will visit this college for placements . I am very interested in AI and deep learning , can anybody suggest how can i get into a product based company with reasonable probability and resume requirements for such job
#engineering #college #machinelearning #AI #productbased
5 answers
G. Mark Stewart
G. Mark’s Answer
I believe I've answered a question very similar to this before. But basically, you would start out with your education. It's highly unlikely that you would have much success getting into a real job with ML without a high school diploma, of course. It would also improve your changes markedly if you got a four-year degree in a related field rather than a two-year degree. That being said, you'd most likely want to choose a major involved with engineering or computer science that covered some mathematics and programming for Machine Learning and general Artificial Intelligence.
The next phase is to do some investigation and research to find out which companies are building products or services based around, or at least requiring a bit of, Machine Learning. Your studies in ML will lead you in the right directions to do that.
Having a degree and putting together a resume showing your study in ML and putting it on job boards on the internet will get you attention. Searching the job listings will be your job, and you'll use that knowledge of current ML efforts and projects by companies to guide you with this as well. As for "product based" or "service based" or what you specifically are interested in in those areas, this work on your part will help tons.
Another thing you might do that most people don't do is contact current employees of companies act may be involved in ML and get their input. At the very least, for any of your contacts that choose to help you out, you'll gain more insight and maybe some useful mentors and contacts. And -- fingers crossed -- future co-workers.
Anna Vinogradova
Anna’s Answer
Take an AI course https://www.elementsofai.com/
Build AI/ML products on your own or with a team, put into your portfolio and post on social media
Tianxin Shao
Tianxin’s Answer
Besides study ML/AI technology, you had better to study statistics knowledge and basic coding skills, like Python, Shell. To find the interested industry, for example: financial, medical, etc. You shall have some knowledge on this industry then you will try ML/AI solution to solve their paint point.
Kaggle https://www.kaggle.com/ is also good platform for you to learn some successful ML cases
James Constantine Frangos
James Constantine’s Answer
Here's a Guide on Securing a Position in Machine Learning within Product-Based Companies:
1. Establish a Robust Base: Solidify your grasp on machine learning, artificial intelligence, and deep learning basics. This includes understanding algorithms, data structures, statistics, and common ML programming languages like Python and R.
2. Accumulate Hands-On Experience: Practical experience is key in machine learning. Engage in AI and deep learning projects to display your competencies. Join hackathons, Kaggle contests, or contribute to open-source projects to exhibit your proficiency.
3. Seek Higher Education: Consider advancing your education with a Master's degree or Ph.D. in machine learning or a related discipline. Such degrees equip you with specialized knowledge and research opportunities, making you more attractive to potential employers.
4. Network Actively: Participate in industry events, conferences, workshops, and meetups centered around AI and machine learning. Connecting with professionals in the field can lead you to job opportunities and potential referrals.
5. Craft an Impressive Resume: Customize your resume to emphasize your machine learning skills and experiences. Include information about projects you've completed, programming languages you're skilled in, any certifications you've earned, and relevant internships or work experience.
6. Gear Up for Interviews: Practice coding challenges, technical interviews, and commonly asked behavioral questions for machine learning roles. Be ready to talk about your projects in depth and showcase your problem-solving skills.
7. Apply with a Strategy: Research product-based companies that emphasize AI and machine learning, and apply to roles that match your interests and abilities. Use job boards, company websites, and professional networking platforms to discover job vacancies.
By adhering to these steps and consistently enhancing your machine learning skills and knowledge, you can boost your odds of landing a job in a product-based company specializing in AI.
Top 3 Credible Sources Used:
IEEE Xplore: This digital library offers access to top-notch technical literature in engineering and technology. It provides research papers, conference proceedings, standards, and educational resources on machine learning and artificial intelligence.
Towards Data Science: This widely recognized online platform publishes articles on data science topics like machine learning, deep learning, AI applications, and more. It offers insights into industry trends, best practices, tutorials, and career guidance for budding data scientists.
Stanford University’s Online Courses: Stanford University provides online courses on platforms like Coursera, covering various aspects of machine learning. These courses impart valuable knowledge and practical skills crucial for a career in AI-related fields.
May God Bless You!
JC.
