Machine learning is an exciting field to work in, owing to the fact that its popularity is increasing every day. There are various data scientists that dedicate all their time to build a successful machine learning career, the reason being higher salary and huge demand. As per a recent report, the average salary for an ML engineer is $146,085 and almost every sector has a multitude of applications when it comes to machine learning and artificial intelligence, such as manufacturing, finance, transportation, retail, etc. So if you have been waiting to build a career in one of the most in-demand fields, now is the right time to pursue a career in ML.
Top career paths in ML
When you gain a good level of machine learning skill, you open new doors of opportunities for you in terms of better job profiles and higher than average salaries. Here are some of the prominent careers in the ML field that you can explore:
- ML Engineer: If you have knowledge of Python, Scala, and Java then you can become an ML engineer easily. The job needs you to be familiar with statistics and probability, ML algorithms, and data modeling as well. You would be writing software programs for different purposes like network distribution, operating systems, and converting a program into executable files.
- Data Scientist: The main role of a data scientist is to collect, analyze, and sort a huge amount of data to produce actionable insights. ML is an important skill for any data scientist, as it helps with data mining and deriving in-depth knowledge of various research techniques. You also need familiarity with Hadoop, Spark, Hive, and Pig so you can create a perfect data map using the provided data set.
- NLP Scientist: They play a vital role in the development of machines that learn from human speech and then carry out different actions based on the command. This kind of technology is becoming hugely popular in fields like media, finance, the healthcare industry, and human resources. You need fluency in spelling, grammar, the syntax of at least one language along with ML skills to become a good NLP scientist.
- Human-Centered ML Designer: As the name suggests, it involves creating ML algorithms based on human experiences and knowledge to achieve desired results. As an ML designer, your job would be to recognize patterns and make machines able to learn the individual human preference without encountering any lag. The real examples of this application are Facebook, Instagram, and Twitter feeds that change based on individual usage history.
How to begin your journey in ML?
You need to have patience above everything else while beginning your journey. Focus on understanding the basics before moving on to advanced topics. Since ML and AI are the fields that are upgrading every day, the learning cannot be contained in a three or four month’s course. So, the important thing is to keep learning for several years. Here are some suggestions for the beginners:
- Understand the field: It may sound obvious, but before you make any future decision you should know what ML is all about. Are you driven and motivated enough to work on regular projects? Do you like the technologies involved? Are you good with mathematics and probability? The first step is to introspect and self-evaluate.
- Be curious: As mentioned above, it is a vastly growing field that keeps updating every few days, so there will be a lot of new challenges and learning opportunities for you in the future. But are you curious enough to explore and learn most of them? Without that zeal, your professional growth may not be as good as you imagined it to be.
- Learn Python and using ML Libraries: For a smooth ML journey, you need to be familiar with Python and various ML libraries, as it is a prerequisite for any job profile you would apply for in the field. It is possible to become an expert with the knowledge of one language only, but you need to have a good grasp of it to be successful.
- Attend an ML Bootcamp: Machine learning bootcamps can help you gain all the relevant skills as soon as possible to make you a professional. There are various Machine Learning bootcamps that specialize in ML training by teaching data analytics, big data Hadoop, Python programming, and even strengthen your expertise in associated libraries and frameworks. One of the best camps is SynergisticIT that helps you gain an in-depth knowledge of this emerging field along with providing you hands-on practical experience.
A lot of companies are working their way to implement AI and ML in their business models and only 11 percent of them have by far achieved it. It means there is a huge scope for aspiring ML aspirants once they gain the required skill-set. So begin your journey today and be a part of this promising sector.
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Build a Successful Machine Learning Career! - Articles - Machine Learning Bootcamp
