Machine learning (ML) and artificial intelligence (AI) are the reigning domains in the digital world today. These technologies can completely transform the way any business is conducted. As the business-wide adoption and business applications of both AI and ML are increasing, many IT professionals are opting for these domains as their careers. In 2021, there were thousands of online inquiries for an Artificial Intelligence course in Mumbai. However, some skills and certifications are considered necessary to stand out in a pool of applicants. In this article, let us look at the skills you must hone and the certifications you must earn to get hired as a machine learning engineer, AI developer, or research scientist.

Skills Required for a Career in Machine Learning and Artificial Intelligence 

Since Machine learning and AI jobs usually come with extensive development of algorithms, requiring adept problem-solving and analytical skills. Hence, a graduate, master’s, or doctoral degree in Computer Science or equivalent certifications to prove your mettle with high-level programming and analytical skills is considered ideal for a beginner in the AI and machine learning domains. Take a look at the top skills required to build your career in artificial intelligence in the below paragraphs.

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  1. Statistical Skills 

Statistical methods are the most popular tools to derive insights from large quantities of information, which is one of the main tasks of Machine learning tools today. Moreover, common AI models like Gaussian Mixture Models, Hidden Markov Models, Naïve Bayes, etc., are based on complex statistical theorems and proofs. So, good statistical skills make better AI professionals. 

  1. Mathematical Skills and Probability 

Apart from statistics, AI as a field also requires applied mathematical concepts such as sets, probability, calculus, etc. Moreover, excellent analytical and problem-solving skills are a must in the AI profession; these are generally the forte of mathematics prodigies. 

  1. Programming Skills 

Good math knowledge is only half the requirement to work in AI; the other half is strong programming skills. Adeptness in programming languages like Java, C++, Python, and R is necessary to make the overall coding process faster. Python is another go-to choice for ML developers as it offers various libraries and frameworks that enable the easy creation of an AI model. R and Java are, respectively, helpful for understanding stats and implementing mappers. 

  1. Advanced Signal Processing Techniques 

AI and ML engineers must be familiar with various advanced signal-processing techniques. Digital signal processing has seen revolutionary changes with the rise of AI through techniques like layered signal representations, nonlinear signal prediction, and nonlinear function approximation. Aspirants must have a working knowledge of different algorithms such as curvelets, bandlets, and shearlets for more efficient feature extraction. 

  1. Distributed Computing 

AI jobs consist of dealing with large and complex datasets, which a single machine would struggle to process. These datasets need to be equally distributed across an entire cluster; hence distributed computing knowledge becomes significant in AI. Professionals need to possess expertise in applications like MongoDB, in creating and operating cloud environments, and in Unix tools. Moreover, they need decent data modeling and evaluation skills.

Career Paths in Machine Learning and Artificial Intelligence 

AI and ML offer five major career paths for you to choose from. We’ll take a look at each one of them in detail. 

  1. Machine Learning Engineer 

Machine learning engineers handle the management and building processes of machine learning platforms. They must be skilled in programming languages like Python, Java, and Scala. Moreover, ML engineers must know how to manage large amounts of data using tools like R and SQL. Aspiring professionals will also benefit from experience in agile development practices and familiarity with leading development tools like IntelliJ, Eclipse, etc. 

  1. Data Scientist 

Data scientists handle the collection, analyzing, and interpretation of large and complex datasets of an organization using predictive analytics and machine learning. Additionally, they implement new machine learning models to enable the organization to make timely and effective decisions. They must be familiar with tools like Spark, Pig, MapReduce, Hive, Hadoop, etc., and with programming languages like SQL, Python, Perl, and Scala. Moreover, familiarity with cloud utilities like Hadoop or Amazon S3 is considered an advantage. 

  1. Business Intelligence (BI) Developer 

Business intelligence developers are tasked with analyzing complex data sets to identify market and business trends. Further, these developers model, design, and maintain complex data using highly-accessible cloud data platforms. Strong analytical, as well as technical skills, are a must for this position. And candidates should are expected to be familiar with SQL queries, data warehouse design, data mining, and BI technologies.  

  1. Research Scientist 

A Research scientist is a master of multiple AI disciplines, including deep learning, computational statistics, machine learning, and applied mathematics. Thorough knowledge of graphic models, natural language processing, computer perception, and reinforcement learning are requisites to occupy this position. Moreover, a good understanding of distributed computing and parallel computing is beneficial. 

  1. Big Data Engineer/Architect 

Big data engineers (big data architects) design, plan, and develop big data environments on Spark and Hadoop systems. They must be experts in configuring databases, distributed computing deployments, etc. A good grasp of languages like Java, Python, C++, and Scala is useful, and so is an in-depth knowledge of data mining, data virtualization, and data migration.


So, as you can see, there are myriads of ways in which you can enter the Data Science or Machine learning domain. However, all these paths require expertise in some programming and analytical skills. The best way to develop these skills is through a recognized certification that offers relevant industry exposure and placement assistance. Simplilearn has been known to provide world-class certification training in subjects like AI and ML for over a decade. Some of our courses and Bootcamps have been ranked number 1# in the world by multiple ranking agencies. So, sign up for the AI & ML course from Simplilearn to start your dream journey today.