How to succeed in pursuing a Machine Learning career?

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Machine Learning has taken over the world to a great extent. As per Forbes, the global market of Machine Learning is expected to reach $20.83B by 2024. The increased adoption of Machine Learning shows the efficiency of its algorithms, techniques and frameworks in solving complex problems. As Machine learning is reforming the business landscape, it drives the demand for professionals. Machine Learning expertise has become the most in-demand skill in today’s technical sphere. It is claimed to be a consistent and well-paying source of employment that will sustain for decades to come. 

Are you also thinking to commence a career in Machine Learning, yet clueless where to start from? We are here to guide you through the whole procedure, determining the career paths and skills required to be a Machine Learning professional.

Machine Learning is an application of AI that enable computers to do certain tasks like planning, prediction, recognition, diagnosis & robot control without being explicitly programmed. It mainly focuses on advancing computer programs and teaches to make accurate prediction when fed data.

Presently, Machine Learning empowers various services, search engines, voice assistants and recommendation systems including YouTube, Google, Netflix, Siri, Alexa Spotify and social media feeds such as Twitter & Facebook.

In order to drive remarkable job opportunities in the field of Machine Learning, you need to acquire many skills as mentioned below:

In addition to the above technical skills, it is essential to procure some soft skills or behavioral skills to start a Machine Learning career like:

Once you acquire the right Machine Learning skills, it will open a door for several career options for you. Some of the promising career paths in the field of Machine Learning are as follows:

Machine Learning Engineer– The fundamental duty of a Machine Learning Engineer is to design & develop Machine Learning systems by using suitable tools, libraries, programming languages and algorithms. ML Engineers analyzes data to create numerous self-directed algorithms that runs with a little human supervision. For this job position a person needs to be competent in probability, statistics, data modeling, system design, ML algorithms, and programming.

Data Scientist- Data Scientists are required to collect, analyze and interpret voluminous data for finding actionable insights. A Data Scientist incorporates Machine Learning algorithms to find the meaning in the data. Also, they look for the problems and provide appropriate solutions. This position requires higher knowledge of Big Data platforms such as Hadoop, Hive, Spark, Pig and programming languages like Python, SQL, etc.

NLP Scientist/Computational Linguist- Another propitious career opportunity in the Machine Learning domain is NLP Scientist or Computational Linguist. In our daily regime we use several voice recognition systems and speech to text applications which are mainly based upon Machine Learning. Computers systems learn patterns of speech and understand human languages through computational linguists. So, the job of a Computational Linguist or (NLP) Natural Language Scientist is to create machines that can swiftly learns the pattern of speech, thereby translate words into spoken languages. To become an NLP Scientist, you have to develop strong understanding of the syntax, grammar, and spellings of at least 1 language in addition to Machine Learning.

Human-Centered Machine Learning Designer- As its name suggests, a Human-Centered Machine Learning Developer is dedicated to design intelligent systems that can learn the behavior patterns & preferences of individuals through pattern recognition & information processing. Some popular examples of such intelligent systems are Netflix, Amazon recommendations and Spotify. For this particular job, you are required to learn in-depth Machine Learning concepts, how they function along with coding proficiency.

Machine Learning/AI Software Developer- Just like any other software developer, a Machine Learning or AI Software Developer needs to have robust coding skills to develop algorithms. They are predominantly responsible for creating flow charts, models, and diagrams that streamlines the jobs of coders. Software developers are commonly called as creative heads behind computer programs as they design underlying infrastructures to regulate specific computer functions.

ML Developers considers various components of a system and decides how it should work. This job role requires an ability to determine how to implement algorithms for a system to perform specific functions. Also, it calls for a deep understanding of data structures and computer architecture concepts.

The growth rate of Machine Learning is spectacular and it is all set to gain more prominence in the near future. With increasing popularity of Machine Learning many technical enthusiasts are thriving to step into the industry.  

If you possess a real-world experience and required skills, the road to becoming a Machine Learning professional seems to be easy. Pursue a stead career in Machine Learning with our support. We provide an upskill program in Machine Learning that covers all the basics to advance level ML concepts.

Let’s help you achieve your career goals. SynergisticIT- The Best Programmers in the Bay area…Period!