試す 金 - 無料
Universities need to invest in AI infrastructure
DataQuest
|March 2025
Suchismita Sahu, Senior Data Scientist at Nvidia, has navigated the competitive world of AI, building expertise in deep learning, speech and image processing, and large-scale Machine Learning applications. In this interview, she shares the essential skills for AI professionals, and how fresh graduates can position themselves for success in a dynamic, tech-driven world.
What advice do you have for aspiring data scientists, and key skills required to excel in the AI industry.
My advice for aspiring data scientists is to be curious, persistent, and always learn. Build a strong foundation in math, statistics, and computer science. Develop your programming skills and gain experience with AI/ML tools and techniques. Seek out opportunities to work on real-world projects and collaborate with others.
Key skills required to excel in the AI industry include:
- Strong programming skills (Python, etc.)
- Knowledge of AI/ML frameworks (TensorFlow, PyTorch, etc.)
- Understanding of statistical modeling and Machine Learning algorithms
- Ability to communicate effectively and work in a team
- Problem-solving and critical-thinking skills
- Continuous learning and a passion for AI
“Even though programming language proficiency can now be aided by LLMs, a strong grasp of algorithms, data structures, and analytical problem-solving remains essential. Companies seek professionals who can navigate the intersection of technology and human interaction, combining technical expertise with effective communication.
How are colleges aligning with industry demands through curriculum updates, internships, and research collaborations?
Colleges are actively bridging the gap with industry through different ways. We're seeing curriculum updates that incorporate the latest tools and techniques, ensuring students learn relevant skills and apply them.
Internships are becoming increasingly vital, providing hands-on experience and a real-world understanding of industry challenges. Finally, research collaborations between universities and companies are fostering innovation and allowing students to contribute to cutting-edge projects, making them highly sought after upon graduation.
このストーリーは、DataQuest の March 2025 版からのものです。
Magzter GOLD を購読すると、厳選された何千ものプレミアム記事や、10,000 以上の雑誌や新聞にアクセスできます。
すでに購読者ですか? サインイン
DataQuest からのその他のストーリー
DataQuest
Empowering India's Al future through data: Snowflake's Vijayant Rai on innovation, collaboration, and talent
Snowflake India MD Vijayant Rai shares how the company is unifying data, advancing AI innovation, and skilling the next generation for a data-first India.
6 mins
December 2025
DataQuest
How AI is redefining delivery in the digital engineering era
As AI reshapes software engineering, delivery models are evolving from effort-based execution to intelligent, outcome-driven systems that blend human and machine collaboration.
3 mins
December 2025
DataQuest
NetSuite's Global Vision: Building the Intelligent Enterprise for the Al Era
At SuiteWorld 2025, NetSuite unveiled an AI-first vision with embedded assistants, customizable AI workflows, and global expansion focused on balancing innovation, trust, and local market needs.
4 mins
December 2025
DataQuest
V. Rajaraman: The teacher who built India's computing mind, no more
When a teacher departs, the blackboards weep. A generation of learners, spread across the world, pause and go back in time, overwhelmed by a quiet sense of gratitude and loss. Such is life, and such is India’s timeless Guru-Shishya parampara, where many jambavans silently walk the corridors of knowledge, leaving behind an imprint that endures long after they are gone.
5 mins
December 2025
DataQuest
Pilot or Paradox: Where are you parking your Al today?
Fragmented data, model pluralism, lack of a fabric, not enough skills, model economics, model volatility and the blank page syndrome- everything matters when it comes to making sure that an AI pilot does not end up as a paradox. And whether you are in that '5 pc' club?
6 mins
December 2025
DataQuest
QA engineers must think like adversaries
What happens when Ramp-testing a vehicle happens around the assembly line, earlier-faster-deeper-and-smarter than before? And as ruthless as a crash-test?
4 mins
December 2025
DataQuest
Why data readiness defines GenAl success: Krish Vitaldevara, Informatica
Informatica's Krish Vitaldevara explains data readiness gaps, CLAIRE's evolution, multi-cloud neutrality, governance for GenAI, ROI metrics, and the impact of the Salesforce acquisition.
7 mins
December 2025
DataQuest
Customer Zero to Global Impact: Salesforce's Playbook for Intelligent Enterprise Transformation
At Dreamforce 2025, Salesforce unveiled Agentforce 360, highlighting how context-aware AI agents are driving measurable business transformation across India and ASEAN.
3 mins
December 2025
DataQuest
DisCERNing Quantum – And not as some Shiny-Pink Uni-saurus
Noise control, fault tolerance, error-correction, superconducting circuits, trapped ions, photonic systems, hardware stability, hardware scalability, algorithmic maturity, strong-enough qubits - everything matters when it comes to the difference between reality and disillusionment with the Quantum Advantage.
6 mins
December 2025
DataQuest
Improving Efficiency and Supplier Relations through Accounts Payable Automation
AP automation transforms accounts payable from a cost centre into a strategic enabler, driving efficiency, transparency, and stronger supplier relationships.
4 mins
December 2025
Listen
Translate
Change font size
