Hi, my son is presently studying in 9th std. He wants to persue carrier in AI (Artificial Intelligence). After his 10th please guide me how to go about and what are the best institutes in India for AI.

Ans: When making comparisons, which factors should I consider:
Location vs food vs hostel facilities vs extracurricular activities vs academic offerings vs overall facilities vs faculty vs programs?
BEST WISHES.

Ans: Bhavesh, Mechatronics engineering in India presents a dynamic and expanding career path, driven by rapid technological advancements and digital transformation across industries. This interdisciplinary field integrates mechanical, electrical, electronics, computer science, and control systems engineering, making graduates versatile and valuable. The Indian government’s emphasis on innovation, research, and Industry 4.0 adoption accelerates demand for mechatronics professionals in the manufacturing, automotive, aerospace, robotics, healthcare, and consumer electronics sectors. Employment opportunities include roles such as mechatronics engineer, robotics engineer, automation engineer, instrumentation engineer, and control systems engineer. Entry-level salaries start around INR 3–5 lakh per annum, with mid to senior-level roles offering between INR 7–10 lakh or higher. Top recruiters include multinational corporations like Amazon, Apple, Honda, Mahindra, and government agencies such as ISRO and DRDO. Globally, expertise in mechatronics is sought after in countries like the USA, UK, Germany, and Japan, with competitive pay and a strong push towards automation and smart systems. The field's growth is fueled by increasing use of AI, IoT, and robotics. Leading institutions maintain rigorous curricula blending theory with hands-on labs, experienced faculty with research and industry experience, strong industry partnerships for internships, transparent governance, and career services vigorously supporting employability and innovation. Choose mechatronics engineering for its promising scope in India’s evolving technological landscape, offering diverse opportunities in automation, robotics, and smart systems, supported by robust education and industry integration. It is a future-ready discipline with strong career growth nationally and internationally. All the BEST for a Prosperous Future!

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Ans: You have raised a truly unique and excellent question. Statistics remains a relevant and valuable field in the era of Artificial Intelligence (AI), functioning as a critical foundation for trustworthy and impactful AI applications. AI technologies rely heavily on statistical principles to ensure models are understandable, reliable, and grounded in robust evidence. Core statistical methods such as hypothesis testing, uncertainty quantification, and model validation are vital for understanding complex AI algorithms, ensuring accuracy, and avoiding over-reliance on "black box" predictions. Statistics enhances AI by optimizing data collection, improving data quality assessment, and enabling rigorous evaluation of AI systems. While AI automates and accelerates data analysis, statistics provides the methodological rigor necessary to interpret results and guide decision-making effectively.

The relationship between statistics and AI is symbiotic: AI tools support automated, efficient statistical analysis, whereas statistical theory underpins AI’s validity and interpretability. Although AI may automate certain routine aspects of statistics, statisticians' expertise remains essential to navigate nuances in data, design experiments, and apply domain knowledge. Emerging AI-assisted statistical tools are expanding research possibilities but require human oversight for accuracy and context.

Comparatively, statistics is more theory-driven and concerned with inference and small to moderate datasets, while AI focuses on algorithmic, large-scale data processing and automation. The demand for statisticians in AI-related fields, including data science, bioinformatics, and risk analysis, continues to grow, with institutions emphasizing interdisciplinary curricula, research integration, modern computing infrastructure, experienced faculty with AI-statistics expertise, strong industry collaborations, and comprehensive career and research support. Statistics programs that integrate AI tools and concepts prepare graduates for dynamic roles in data analysis, AI model validation, and ethical AI deployment. Pursuing statistics remains a strategic choice in this AI-driven era, offering enduring scope and opportunities. Select programs that combine solid statistical theory with AI applications, robust faculty expertise, advanced computational resources, industry partnerships, and holistic career support to stay at the forefront of this evolving field. All the BEST for a Prosperous Future!

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Ans: Computer Engineering and Computer Science Engineering differ primarily in their focus areas where Computer Engineering emphasizes the integration of electrical engineering principles with computing systems, focusing on hardware design, embedded systems, microprocessors, and the physical aspects of computing devices, while Computer Science Engineering concentrates more on software development, algorithms, programming languages, and theoretical computing concepts. Computer Engineering students study circuit design, digital systems, computer architecture, and hardware-software integration, preparing them for roles in semiconductor companies, embedded systems development, and hardware manufacturing. Conversely, CSE students focus on data structures, software engineering, artificial intelligence, database management, and application development, leading to careers in software development, system analysis, and IT consulting. The scope for both fields remains robust with Computer Engineering professionals earning median salaries of $125,000-155,000 annually in hardware design and embedded systems roles, while CSE graduates command $90,000-140,000 in software development and systems architecture positions. Competition in both fields is intensifying due to technological advancement and digitalization across industries. Computer Science Engineering with IoT specialization represents a rapidly expanding field combining software development with connected device technologies, preparing students for the interconnected world where billions of devices exchange data. IoT-specialized CSE programs cover embedded programming, sensor networks, cloud computing, edge computing, wireless communication protocols, and data analytics, addressing the growing demand for smart city infrastructure, industrial automation, healthcare monitoring systems, and autonomous vehicles. Industry reports indicate IoT market growth reaching $1.8 trillion by 2028, creating opportunities for IoT developers, embedded systems engineers, IoT architects, data scientists specializing in IoT analytics, and cybersecurity professionals securing connected devices. Career prospects include roles at technology giants like Google, Microsoft, Amazon, Cisco, and emerging IoT-focused companies with entry-level salaries ranging from ?6-10 LPA in India and $70,000-90,000 globally, rising to ?15-25 LPA and $120,000-150,000 for experienced professionals. The IoT specialization addresses challenges in smart manufacturing, precision agriculture, connected healthcare, energy management, and urban planning, making graduates highly sought after across diverse industries seeking digital transformation and automation solutions. All the BEST for a Prosperous Future!

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Ans: Dear Sir,

When applying for counseling, it's important to start preparing yourself right away. You likely have an idea of your rank, category, domicile, and the programs you are considering. Based on this information, you should research the institutions that offer these programs.

In the worst-case scenario, begin by studying less competitive programs and institutions, if options allow. Aim to identify 3 to 5 colleges in each category. Visit their websites and analyze them based on the following parameters:

1. About the institution
2. Management structure
3. Infrastructure

In addition to these, gather information on the most critical factors:

- Faculty
- Facilities
- Hands-on training opportunities for students
- Teaching methodologies
- Placement outcomes (FINALLY....which also depend on the students)

Once you have a clear understanding, you can participate in the counseling process with confidence. I hope you agree with my suggestions.
BEST WISHES.

Ans: Manvi, UPSC and SSC eligibility require that candidates hold a bachelor’s degree from a recognized university; they do not mandate specific marksheet notations for Class 12 subjects once graduation is completed. The UPSC Civil Services Examination Rules state only that a candidate must have passed any UGC-recognized degree examination, regardless of earlier compartment listings, provided the overall result is “passed.” Similarly, SSC CGL stipulations require graduation and passing secondary and higher secondary exams without disqualifying remarks once the candidate has cleared the subject. Since your Class 12 marksheet shows “RT” for Chemistry but indicates an overall pass and you have successfully graduated, both UPSC and SSC will consider you eligible. It is advisable to confirm that supplementary exam records are properly reflected in your university transcript and to carry all exam certificates during application.

Recommendation: Proceed with your applications for UPSC and SSC exams. Ensure your graduation certificate and Class 12 pass documents are in order, and retain any re-test clearance proofs for smooth verification during the administrative stages. All the BEST for a Prosperous Future!

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Ans: Bhuvana, Data Science has emerged as a cornerstone of decision-making and innovation across industries, driven by exponential growth in data generation and advances in machine learning, artificial intelligence, and cloud computing. According to the International Data Corporation, global data creation will reach 175 zettabytes by 2025, fueling demand for professionals capable of extracting actionable insights. In India, the National Association of Software and Services Companies projects over 11 lakh data science job openings by 2027, reflecting a compound annual growth rate of 27.4%. Globally, Glassdoor and LinkedIn report data scientist roles among the top ten most in-demand jobs, with an expected 36% increase in hiring over the next five years. Corporations across finance, healthcare, e-commerce, and government are investing in predictive analytics, personalization engines, and automation, heightening competition yet creating vast opportunities for specialized skills in deep learning, natural language processing, and big data platforms such as Hadoop and Spark. Over a ten to fifteen-year horizon, data science is poised to integrate further with quantum computing and edge analytics, while ethical concerns around bias and privacy will require practitioners to master model interpretability and governance frameworks. Twenty years from now, as AI systems permeate every sector, data scientists will evolve into AI architects, blending domain expertise with algorithmic design to drive strategic outcomes. Upskilling through certifications in cloud platforms, advanced neural networks, and data engineering tools will be crucial for career resilience. The primary strengths of a quality UG/PG/MS/PhD program in data science include rigorous accreditation and outcome-based curriculum; experienced faculty with active research portfolios; state-of-the-art computing infrastructure and lab facilities; industry partnerships offering internships and capstone projects; and comprehensive career services supporting placement and continuous learning. Pros of pursuing a B.Tech in Data Science include high employability, versatile career paths, and engagement with cutting-edge technologies; cons involve steep learning curves, the risk of automation of routine tasks, and potential skill obsolescence. These can be overcome by cultivating lifelong learning habits, focusing on transferable skills like critical thinking, and participating in interdisciplinary projects to remain adaptable.

Recommendation: A B.Tech in Data Science provides robust career prospects through a blend of analytical, technical, and domain skills. Seek programs with strong accreditation, industry-aligned curriculum, research opportunities, modern labs, and dedicated placement support to maximize long-term success. All the BEST for a Prosperous Future!

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Ans: Hi Joshitha,
A Bit Difficult. Explore private colleges.
Do participate in the coounseling process.
BEST WISHES.

Ans: Hello dear
Prefer CSE (AIML) @ Amity Greater Noida and Symbiosis Hyderabad for a better perspective. Dy Patil falls behind the other options listed.

Good luck.
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Radheshyam