Megan Nangaonkar
It’s the age of artificial intelligence (AI) and machine learning (ML). AI is considered one of the most revolutionary technological developments of our time. Beyond tech giants and other major industries, AI is also embedded in our daily lives through gadgets, social media, smart home his devices, banking and more. It won’t be long before AI and ML-enabled machines impact every area of our lives.
Artificial intelligence is the construction of computer systems that can simulate human intelligence. It helps computer systems perform tasks and make decisions and choices without relying on human intervention. Related technologies such as machine learning cover techniques that allow systems to develop the necessary intelligence. With ML, systems learn from past data and experience without being explicitly programmed. As the fields of AI and ML continue to evolve, they will continue to offer a ton of job opportunities. In India, AI is estimated to create 900,000 white-collar jobs and 3.6 million indirect jobs by 2030.
Here are eight skills that anyone looking to build a career in AI and ML should have.
Mathematics: Good mathematical skills are essential for any AI/ML professional who deals with applied mathematics and algorithms on a regular basis. AI professionals are also required to decipher huge datasets using mathematical techniques. Combining strong mathematical skills with analytical thinking enables technology professionals to solve complex AI problems. Proficiency in AI/ML programming requires proficiency in statistical or mathematical concepts such as optimization techniques, graphs, probability, linear algebra, calculus, and matrices.
Data Modeling: Data is at the heart of AI and ML, because every program requires a lot of data to run. The more data, the better the results. However, the vast information set, once properly classified, can be leveraged to support data analysis. It is necessary to look at the data and understand important relationships between data points. The data is useful only after applying the right data modeling techniques to give it its final structure, from which important insights can be derived. AI must use data modeling to recognize these patterns and relationships. Through data modeling, enterprises can model information according to their requirements, simplify AI/ML-driven analytical processes, and get better solutions to business problems.
System Design and Architecture: Product ecosystems are created by combinations of machines assembled together. It’s important to understand how each piece fits into the puzzle and how they communicate with each other. A system design or architecture defines the quality attributes of the programs that are built. AI/ML-based systems developed without a proper architecture will fail due to inconsistencies in the system’s behavior on data, dependencies on shared resources, and the environment of various components. Therefore, it is imperative to develop the necessary skills in system architecture to develop desirable AI/ML systems that run smoothly.
Natural Language Processing (NLP) and Neural Networks: AI/ML systems aim to mimic human intelligence and decision-making. Therefore, without the computer’s ability to understand how humans communicate and process information, the system would be incomplete. Neural networks are designed to mimic the functions of the human brain. His NLP of AI/ML systems brings immense capabilities and brings us closer to how humans communicate via different languages. Understanding the basics of NLP and neural networks will give you a head start. AI professionals need to design neural networks, so understanding the system is essential. This helps bring innovation and creativity to your work.
Programming Languages: Learning the languages that computers and data work with is fundamental. Programming languages help computers communicate with various systems. Therefore, candidates should know programming languages used in AI applications, such as shell script, C++, Java, R, and Python.
Domain understanding: A good understanding of industry domains is critical in AI and ML. You need to know the challenges you’re trying to address and why you need AI and ML solutions. Otherwise, your efforts may not be headed in the right direction. It is imperative that AI professionals work with the right stakeholders to understand the business environment and the specific problems they need to solve. More domain knowledge helps experts to put together the right architectures and systems. Good domain knowledge can also help you anticipate future challenges. Learning and honing advanced technical skills requires grit and perseverance. Always keep up with the latest technological advances.
Critical Thinking: In addition to subject matter knowledge, it is important to have critical thinking and analytical skills. This helps AI experts break down the problem into smaller pieces and approach the optimal solution in a simplified way. When it comes to AI and ML, it’s important to be curious, ask the right questions, and make decisions based on trial and error. Critical and analytical thinking skills help you create solutions that address even the most complex business problems.
Communication skills: AI and ML engineers don’t work alone. You are also expected to be a good collaborator, working with other engineers and non-technical departments such as marketing and sales. AI and ML professionals focus on solving business problems. Therefore, it requires working with different teams within the organization to better understand the problem and create appropriate solutions. Proper communication skills also help AI professionals communicate ideas seamlessly and facilitate smooth functioning between teams.
There is no doubt that AI and ML jobs will continue to be in demand. Therefore, it is critical that aspirants invest time and energy in upskilling to future-proof them for successful careers in AI and ML. They also need to stay up to date on the latest developments in the space and the conversations surrounding it. Aside from mastering these eight skills, having fun in the world of technology is just as important. People must be driven by the problems they can solve and their ultimate benefits to individuals and society.
The author is the head of Fujitsu’s JDU, Global Delivery Division.
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