Aashish Mohan is a passionate AI professional with a Master’s degree in Artificial Intelligence and is currently a PhD scholar specializing in Machine Learning.

With extensive experience in AI training and consulting, Aashish has worked across the Telecom, Finance, and Retail industries. Over the past eight years, he has played a pivotal role in the AI revolution, collaborating with industry pioneers. As a lead in-house AI, ML, and Analytics trainer, he has conducted training sessions for Microsoft, Cisco, Infosys, Walmart, and JP Morgan Chase, among others.

Aashish has had the privilege of being trained by some of the best analytics mentors at IISC Bengaluru. His contributions to AI education extend to platforms like Udemy, Coursera, and EC Council, where he has shared his expertise with thousands of aspiring Machine Learning Engineers—many of whom have gone on to work at top companies such as Amazon, Google, Cisco, and Facebook.

In all his training sessions, Aashish integrates real-world industry experience, ensuring that even the most complex topics are made accessible and practical. His deep passion for Artificial Intelligence trends drives his commitment to educating and empowering the next generation of AI professionals.

Featured Training Programs:

• ML for Cybersecurity

• Machine Learning Complete Course – A full-spectrum course covering core ML algorithms, data preprocessing, model evaluation, and deployment, designed to enhance in-house team capabilities.

• Generative AI – Principles and applications of Generative AI, including GANs, VAEs, and real-world use cases in content generation and creative AI.

• Applied AI and MLOps – Practical training on implementing AI solutions with MLOps practices, ensuring scalable, reliable, and efficient AI deployments in production environments.

• Statistics for Data Science & Business Analysis – Essential statistical methods for data-driven decision-making, covering hypothesis testing, regression analysis, and predictive modeling.

• AI & MLOps Fundamentals Training – An introduction to AI and MLOps fundamentals, focusing on integrating AI models into operational systems for seamless AI adoption.

• Computational Mathematics for Data Science – Key mathematical concepts required for data science, including linear algebra, calculus, and optimization methods critical for ML algorithms.

• NLP & Other AI Techniques – Training on Natural Language Processing (NLP) and other AI techniques, exploring text analysis, sentiment analysis, and language models like BERT and GPT.

Aashish Mohan remains dedicated to advancing AI education and sharing his expertise with professionals and organizations worldwide.