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5 AI Skills Every Startup Needs to Thrive in India’s Booming Tech Industry
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5 AI Skills Every Startup Needs to Thrive in India’s Booming Tech Industry

Artificial intelligence, AI, is all around us, sometimes working behind the scenes and making our lives convenient. It is rapidly transforming and revolutionizing industries across the globe, from healthcare to finance, which is increasing the demand for AI professionals. According to a recent report, Indian AI experts expect the figure to double by 2027 and the growth of the AI ​​industry is estimated to be in the range of 25-35%.

The technology sector is a highly dynamic arena that challenges those who want to pursue a career in artificial intelligence to hone their skills.

In case you are a recent tech graduate looking forward to building your career in the tech industry and are confused about how to get started, then you should master the necessary skills like data science and management, machine learning and deep, coding and programming as well as Mathematics and Statistics that are relevant in the field.

Pankaj Kumar, Managing Director of Shard Center for Innovation, talks about some essential AI skills for beginners, from programming to hands-on experiences, that not only open doors to opportunities but also advance a career in an ever-changing industry.

1. Programming and Coding

Understanding programming is fundamental for someone interested in pursuing a career in AI. Additionally, learning and mastering programming and coding involves a fairly in-depth understanding of programming languages ​​like Python and TensorFlow, PyTorch and sci-kit-learn. C++ and JAVA knowledge will also be a plus, depending on the specific area of ​​AI you choose to work on.

2. Data management and data science

AI works on a large amount of data for training and testing, extracting meaningful information from the raw data to increase model accuracy. Using tools for collecting, storing and manipulating data alongside Python packages such as Pandas and NumPy and visualizing data using libraries such as Matplotlib and Seaborn will be an added advantage, especially with data cleaning and preprocessing.

3. Natural Language Processing (NLP)

Competencies in NLP involve working with textual data through tasks such as sentiment analysis, language translation, and chatbot development. Key concepts include word embedding, sequence-to-sequence patterns, and various sentiment analysis techniques. Increasing demand for chatbots, linguistic models and AI text-based analysis is increasing the professional demand in this field.

4. Machine learning and deep learning

Being the core of AI, understanding and learning key algorithms in Machine Learning such as regression, clustering, neural networks, decision trees and support vector machines. Also, for Deep Learning, understanding the basics, including feedforward neural networks, backpropagation, and convolutional neural networks (CNNs), is crucial.

5. Mathematics and statistics

Building intuition in mathematics and statistics is essential for effective implementation of AI models. A solid understanding of linear algebra, probability, and calculus is critical because these concepts are fundamental to machine learning. Understanding vectors, matrices, and tensor operations is key to neural networks, while probability and statistical inference guide model evaluation. Mastery of derivatives and gradients is crucial for optimizing machine learning algorithms.

To thrive in the tech industry, having soft skills in problem solving and critical thinking, continuous learning and skill development, and hands-on experiences through projects and internships give you an added edge. As a career in AI is both demanding and highly rewarding, you need to continually update and expand your skills in this rapidly evolving field. As AI advances, it brings ethical challenges and concerns, such as data privacy, algorithmic bias, and its impact on the labor market. Addressing these issues is crucial to ensuring that AI remains a positive force for society.

Combining knowledge of programming, mathematics, machine learning and industry expertise, together with a good level of problem solving and interpersonal communication skills, gives an advantage in this dynamic sector. The future is bright for those with the right attitude and skills, as they will shape the course of AI development.

Posted by:

Apoorva Anand

Published on:

November 17, 2024