AI market can be worth USD 7.8 billion by 2025 | AI career roadmap for beginners – India Today

  • Lauren
  • August 22, 2022
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New technologies like AI, Data Analytics, and Machine Learning have dominated almost every field in today’s ever-evolving high-tech world. With IT companies introducing innovations on a constant basis, the scope for the development of new technologies is limitless.The current AI job outlook is quite promising. As the industry matures, jobs in AI will not only grow in number but also in complexity and diversity. This will open doors for various professionals-junior, senior, researchers, statisticians, practitioners, experimental scientists, etc.WHAT DO STATS SAY?”According to the data collected by The International Data Corporation, the AI market can touch up to 7.8$ billion in India by 2025,” said Ms. Srividya Kannan, Director and Founder, Avaali Solutions.”From a career perspective, through 2023 it is expected that the ML Engineer will be the fastest growing role with open positions for ML engineers at fifty percent of that of data scientists which were less than 10% in 2019,” She added.From being a Data Scientist to an AI engineer and Big Data engineer, the field of AI and Machine Learning offers versatile career opportunities. ML Engineer is the fourth fastest growing job title in the past five years.FROM WHERE TO START Getting enrolled in the right kinds of courses, for example in strategy deployment and automation, is the first step. Then, merely knowing and studying AI is not important. One needs hands-on experience to be able to put their AI knowledge into practice.Here are some of the skills that you would require to make a successful career in the field of AI and Machine Learning. COMMAND ON STATISTICS AND PROBABILITY “To pursue a career in AI, one should have a solid grasp of statistics and probability. It is crucial to have a solid understanding of the statistical techniques used to draw conclusions from data because the majority of AI models rely on identifying patterns in vast volumes of data,” said Dr Somdutta Singh, Founder & CEO of Assiduus Global.”A comprehensive understanding of mathematics and probability concepts is required as AI is a science that uses numerous mathematical principles to build artificial intelligence,” she further added.PROGRAMMING SKILLS Detailed knowledge of programming languages is of the utmost importance. Understanding various forms and scripts of programming, including Python, Java, R, C#, C++, and Julia could be a goal for any aspirant that wishes to enter the AI Industry.FUNCTIONAL EXPERTISE Having a robust technical understanding of AI/ML is imperative, it is equally vital to build aspects of domain knowledge and human expertise to provide context to data.COMPUTING SKILLS AI demands that professionals deal with complex data and algorithms that must be distributed across the entire cluster. Practical knowledge of AI hardware (GPUs and SSDs) and familiarity with public cloud Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). Experience managing systems such as Apache Hadoop and Apache Spark would be beneficial.STATISTICAL EXPERTISE AI is a statics-driven game, and to be an expert, you need to have the capability to understand and analyse statistics to decode complex algorithms. Finding patterns from most of the information available is essential practice for an AI developer.CAREER ROADMAP FOR AI BEGINNERS Students who are currently pursuing this career will likely be on the path of AI/ML engineer, data scientist, developer to prominent data engineer. Aspects of composite AI and practices such as ModelOps (DevOps) and AI Engineering would be great bets for the future.MACHINE LEARNING ENGINEER Machine learning engineers should have a background in combining data science, applied research, and software engineering. Jobs in AI require strong mathematical skills, experience in machine learning, deep learning, neural networks, and cloud-based applications, as well as Java, Python, and Scala programming skills.DATA SCIENTIST A data scientist collects, analyzes, and interprets data for a variety of purposes. Their job is to identify meaningful patterns from data using a variety of technology tools, processes, and algorithms.RESEARCH SCIENTIST In the field of artificial intelligence, the research scientist is considered one of the most academically driven positions. They ask new and creative questions to be answered by AI.BIG DATA ENGINEER Big data engineers and architects develop ecosystems that enable various business verticals and technologies to communicate effectively. In comparison to data scientists, big data engineers and architects are typically responsible for planning, designing, and developing big data environments on Hadoop and Spark.DATA ANALYST In the past, data analysts collected, cleaned, processed, and analyzed data to gain insights. The data analysts of today prepare the data for machine learning models and then build meaningful reports based on the results.If we see that there is a fine line between machine learning and artificial intelligence. One has to understand where they will be deploying their skills. Most engineering colleges include artificial intelligence as a part of their curriculum.However, for the best interests of students who want to start a career in AI or are already in the field of engineering and technology and are looking to build a career in AI, they need to understand that there are specific skill sets that define an AI expert.HELP THE RIGHT COLLEGES FIND YOU!— ENDS —