Integration of AI with existing systems
Why it matters: Explore seamless integration of AI with systems, covering tools, challenges, security, and real-world examples for success.
Sanksshep Mahendra
Sanksshep Mahendra is a technology executive with success in driving, vision, strategy, design, and execution of software engineering for the web, mobile, apps, social, voice, IoT, applications along with Machine learning and AI. His expertise lies in partnering with business leaders, powering through roadblocks, and leading global teams to deliver disruptive products that advance the organization’s mission and capture game-changing results in the market. Sanksshep Mahendra has a lot of experience in M&A and compliance, he holds a Master's degree from Pratt Institute and executive education from Massachusetts Institute of Technology, in AI, Robotics, and Automation.
Ethics in AI-driven business decisions
Why it matters: Explore Ethics in AI-driven Business Decisions: Address biases, accountability, transparency, and societal values.
Handling data privacy and security
Why it matters: Handling Data Privacy and Security: Explore challenges, tools, best practices, and regulatory compliance in AI systems.
Addressing customer concerns about AI
Why it matters: Addressing Customer Concerns About AI: Explore trust, transparency, ethics, and AI benefits for better satisfaction.
Evaluating AI vendor partnerships
Why it matters: Evaluating AI Vendor Partnerships: A guide to choosing vendors, assessing criteria, long-term support, and contracts.
The Complete Machine Learning Lifecycle: A Step-by-Step Guide for 2025
Why it matters: A step-by-step guide to the machine learning lifecycle in 2025, covering key phases and best practices.
Future trends in AI business applications
Why it matters: Future Trends in AI Business Applications: Discover AI’s impact on personalized experiences, automation, and insights.
Building an AI-Driven Business: Strategies and Challenges
Why it matters: Building an AI-driven business: strategies for innovation, managing risks, defining AI opportunities, and scaling success.
Challenges AI faces today
Why it matters: Challenges AI faces today include technical, ethical, and social issues across development, data, bias, and regulation.
Introduction to computer vision
Why it matters: Introduction to Computer Vision: Learn image recognition, AI object detection, and applications in healthcare, vehicles.