Want To Become A Machine Learning Engineer? Learn The Core Of The Data Science Team

“Computers are able to see, hear and learn.  Welcome to the future.” ~ Dave Waters.

Hello Readers,

Welcome to the world of innovation, where algorithms unlock the unlimited secret data of the internet! Sounds unachievable, right? Well, don’t we all want machines to do precisely what we humans are capable of? Don’t we imagine a machine doing all the hard work and us relaxing and enjoying the outcome? Well, so why not help machines grow such uniqueness and change the dynamics of the working world? Today, with the growing demand for such technologies, students of Data Science are experimenting with and discovering new pathways for the futuristic world.

The demand for Machine Learning has grown significantly in the past few years and is expected to increase by 40% between 2023 and 2027. This high demand equals growth in the country’s AI sector, better job opportunities in the field, and, of course, a road to futuristic success.

What is Machine Learning?

Machine Learning is a core and fascinating part of Data Science. It deals with data and algorithms designed to enable AI to think and work like humans. It is intriguing as it involves predicting and grasping outcomes with each new piece of data. The goal is to help machines be affluent in their prognosis about the user’s needs and wants.

It is a broad area that includes everything from video surveillance of the user to facial recognition acquired from smartphones or electronic gadgets. Big companies, mainly social media platforms, use machine learning to target the right audience and check off their interest box.

What do Machine Learning Engineers do?

Have you ever imagined how you get the exact ad of the items you searched on shopping apps or browsed online? Well, that’s the job of the Machine Learning Engineers. Their work involves a lot of researching, building, and designing the artificial intelligence required to support the existing AI and machine learning.

Additionally, machine learning engineers frequently work alongside domain experts, software engineers, and data scientists to comprehend business needs and incorporate machine learning solutions into existing platforms or create new ones. It’s basically like teaching a digital brain how to recognise patterns and make decisions on its own.

How Do You Become a Machine Learning Engineer in India?

The Machine Learning Engineering course may sound daunting and challenging, but it’s easily achievable with dedication and proper guidance. Here are some of the steps that reflect on the requirements and process to become a Machine Learning Engineer in India:

Step 1: Choose the right course:

Every machine learning engineer needs a proper bachelor’s degree to take a step closer to this degree. To understand the dynamics of this course, individuals need to have a degree in one of these subjects: mathematics, data science, computer science, or computer programming. Alternative degrees from relevant disciplines like physics or statistics may also be helpful. It is also essential for Machine Learning aspirants to have a good understanding of business so that they can understand their audience and act accordingly.

Step 2: Proficiency in programming:

To be a Machine Learning Engineer, you must be fluent and proficient in computer programming languages. Python and R are the commonly used languages in machine learning, and thus, it is essential to master these as much as possible.

Step 3: Practical Learning:

This course should focus on more than just theory. This practical learning and experimenting with different types of coding styles and techniques will help the aspirants ace it. Practising with projects and gaining hands-on experience will help boost their chances of getting into this course and help them retain this experience for future job opportunities. The practical learning includes:

• Hands-on Projects: Allowing students to build practical projects that resonate with real-world scenarios can help them better understand the subject. Practical learning can involve starting small projects and moving on to bigger ones.

• Kaggle Competitions: Participating in Kaggle competitions can help one gain the required experience and learn from their mistakes. This may include working on real datasets, solving challenging problems, and learning from the community’s solutions and discussions.

• Internships or Freelance projects: These are some of the best ways to learn from the industry. Interns are often taught like students by industry-experienced individuals. On the other hand, freelancing will help students understand what the client wants from their work, and they can focus on the same.

• Experimentation: Students need to experiment with new ideas and algorithms. Through experimentation, one can come up with something groundbreaking, which this field requires a lot of.

Step 4:  Online Courses and Certification:

Aspirants can opt for certification courses from online platforms like Coursera, edX, Udacity, and Udemy. Some of these certification courses may include the following:

• Coursera’s Machine Learning by Andrew Ng

• Coursera’s Deep Learning Specialization by Andrew Ng

• Google’s TensorFlow Developer Certificate

• IBM’s Applied AI Professional Certificate

Step 5: Develop soft skills:

Soft skills are essential and required for any job. These skills enhance an individual’s qualifications and capabilities. Some of these include:

• Communication: It is one of the primary and most essential skills required in this field. Proper communication can help in collaborative development, explaining complex concepts, documentation of essential subjects, and many more.

• Time Management: This is another essential soft skill that must be instilled in individuals. It helps enhance productivity, reduces stress, and ensures that essential tasks are completed efficiently.

• Problem-Solving: One of the most important soft skills is problem-solving, which involves recognising, evaluating, and addressing problems organisationally. It is crucial in a variety of settings, including both work and daily life, since it helps people overcome obstacles and achieve targets.

• Collaboration: It is crucial in various contexts, such as workplaces, classrooms, and other charitable projects. It has been proven to be the most essential requirement for successful teamwork.

Step 6:  Job Search and Career Growth:

Students must build strong resumes to get a good job opportunity. Some of the required highlights regarding this are as follows:

• Highlight the strengths and skills in the resume. Certificates of participation, previous work experience, and degrees are quite necessary.

• Develop a thorough cover letter to convince recruiters to review your resume.

Also, some popular platforms can help you to land a successful career.

Skills Required to Become a Machine Learning Engineer

Machine Learning Engineer Salary in India: 2024 Career Guide

The salary of a Machine Learning Engineer can vary in India based on the location, level of experience and industry of employment. Each year, the prospect of this has grown and is continuously changing. It will have greater job scenarios in the future. Some of the salary details include:

• Average Salary: 9LPA [Entry level: 6LPA, Mid-level= 10 LPA, Top companies= 40-60 LPA]

• Minimum Salary: 6LPA

• Highest Salary: 40-60 LPA

Takeaway

Machine Learning Engineering requires hard work, passion, and dedication. The course is quite challenging, but with the right mindset, one can achieve anything. Every aspirant needs to get the proper training from the right sector and give their best overall. It is the dream that matters, as diligent effort will inevitably follow.