Category Archives: Programming

🚀 A Guide for B.Tech CS Students to kickstart your AI journey

AI, chatgpt, coding assistants, Programming, , , ,

👋 Introduction

My daughter will be starting her B.Tech in Computer Science at MIT, Manipal this year. As a huge AI proponent, I often share the latest AI trends and tools with my family. When my daughter decided to pursue CS, she asked me several questions about AI, which inspired this blog. I hope this guide helps any student planning to specialize in CS and AI.

📚 Core Fundamentals for CSE Students

Before diving into AI, it’s crucial to master the basics. These are some of the building blocks for everything you’ll do in computer science. Following links will give you an overview of the basics before you deep-dive.

📝 General Advice for Students

In addition to doing your coursework, following tips can help you to be more practically prepared for the industry .

  • Start with Fundamentals: Focus on math, programming, data structures, and algorithms.
  • Build a Portfolio: Work on projects, participate in Kaggle competitions and hackathons, and maintain GitHub repositories.
  • Network: Join AI clubs, attend meetups, and connect with peers and professionals on LinkedIn.
  • Stay Updated: Follow AI news, research, and trends.
  • Internships: Real-world experience is invaluable—seek internships early.

🛠️ Tools to Try Out

Following is just a sample collection at this point of time. The tools change so fast so it’s very important to keep yourself updated with the latest.

  • Chatbots: ChatGPT, Gemini (Try ChatLLM, an aggregator of chatbots and other AI tools collection, its very handy)
  • Vibe Coding: Cursor, Windsurf, Replit, Pythagora (see my earlier blog for more)
  • Image Generation: DALL-E(OpenAI), Midjourney
  • Video Generation: Google Veo
  • ML Platforms: Google AI Studio(Good to experiment with Google AI models), Kaggle(Kaggle competitions are good, good for datasets and notebooks), Hugging Face(Marketplace for models, datasets and easy to share the ML work with others)
  • Automation: Zapier (AI orchestration platform connecting different AI and non-AI tools and platforms)

Note: “Vibe coding” refers to using AI-powered coding environments that help you code faster and more intuitively.

🤖 Exploring AI Domains & Career Paths

Here’s a quick overview of different AI roles, what they do, prerequisites, and how to get started. AI industry is still at its nascent stage, these roles can change as the technology matures.

RoleWhat They DoPrerequisitesHow to Get In
AI ResearcherDevelop new AI models/algorithms, advance the field, publish researchStrong math (linear algebra, stats), deep ML/DL, Python, PyTorch/TensorFlow, research skills, academic writingAdvanced courses (Master’s/PhD), join research labs, open-source, publish papers, attend conferences
ML EngineerBuild, optimize, and deploy ML models in production; manage ML systemsProgramming (Python, C++/Java), ML frameworks, software engineering, cloud (AWS/GCP/Azure), MLOps basicsEnd-to-end ML projects, internships, open-source, learn CI/CD, Docker/Kubernetes, model deployment
Data Engineer/ScientistBuild data pipelines, clean/process data, extract insights, visualize findingsPython, SQL, data wrangling, statistics, data viz, ML basics, big data tools (Spark, Hadoop)Data science/engineering courses, Kaggle, portfolio projects, internships, learn data tools and visualization
AI Application EngineerIntegrate AI models into real-world apps/products; focus on APIs and UXProgramming (Python, JS, etc.), API development, front/back-end, basic ML, UX/UIBuild AI apps, hackathons, internships, learn REST APIs, cloud deployment
AI Security & SafetyEnsure AI systems are secure/safe; address ethical, legal, and risk concernsSecurity fundamentals, cryptography, adversarial ML, AI ethics, risk, regulations, ML basicsCybersecurity/AI ethics courses, CTFs, follow AI safety research, join labs/organizations
AI Product ManagerDefine vision/strategy for AI products; bridge tech and business teamsAI/ML concepts, product management, communication, business acumen, user researchStart as engineer/analyst, PM courses, AI projects, internships, develop leadership/communication
AI Hardware SpecialistDesign/develop hardware/software (GPUs, TPUs, SDKs) for AI training/inferenceECE/CS, digital design, computer architecture, parallel computing, C/C++, CUDA, ML basicsECE/CS courses, hardware internships, FPGA/GPU projects, hardware-software co-design, follow NVIDIA/AMD/Intel

🧑‍💻 AI Basics for Students

Following is just a sample to get started with AI basics.

🤔 How Should College Students Use AI (and How Not To)?

  • Don’t: Use AI chatbots to solve class assignments directly—this can kill creativity and hinder learning.
  • Do: Use AI as a learning tool to explore new ideas, get feedback on completed assignments, and clarify concepts after self-study.
  • Tip: Treat AI as a personalized teacher—seek help only after you’ve tried solving problems yourself.

🔄 Staying Updated with AI

  • Curate Resources: Make a repository of your favorite podcasts, blogs, and YouTube channels.
  • Hands-On Practice: Try new AI tools and work on personal projects.
  • Mix Coding Styles: Combine “vibe coding” (AI-assisted) with traditional coding to strengthen your skills.

💡 Is AI Going to Take My Job?

A typical software engineer spends only 30–40% of their time coding; the rest involves architecture, design, spec reviews, cross-functional discussions, integration testing, and release processes. While AI can assist with coding, these other activities are equally critical and difficult to automate.

Even within coding, engineers must structure code, manage module interactions, choose technologies, debug, test, scale, and deploy—tasks that require human judgment. AI coding tools can boost productivity by 30–40% today, and possibly up to 70% in the next 1–2 years. However, over-reliance on these tools can erode core skills, and poorly organized AI-generated code can become hard to maintain.

There’s no substitute for strong design and coding fundamentals. Use AI tools as an assistant, not a replacement.

Jevons Paradox: If coding becomes much easier and cheaper, we’ll see more coding projects and more coders, not fewer. The demand for skilled engineers will grow as we automate more of the world.

For the next 5–10 years, CS engineers will remain essential. If AI ever surpasses humans in all aspects (AGI), it won’t just be engineers—every profession will be affected.

🌱 Final Thoughts

CS or CS with AI specialization are fields of endless possibility. Stay curious, keep building, and remember: the journey is as important as the destination. Embrace change, focus on fundamentals, and use AI as a tool to amplify your learning and creativity.

Wishing all new B.Tech CS students an exciting and rewarding journey ahead!

Picture with my lovely daughter!

Ansible for Network Automation – Part 2

Ansible, cisco, devops, devopsnet, Jinja2, Programming, python, UCS, yaml

This blog is part of my series on Devops for Networking. In the previous blog, I covered basics of Ansible and how to get started with it. In this blog, I will cover a sample application that I wrote with Ansible. This Ansible application builds on UCS sdk utility that I covered in a previous blog. The UCS python utility displays the inventory of UCS system. I have made that utility as an Ansible module and extended the application to display the inventory of a list of UCS systems that are defined in the host list. This project is more to illustrate the usecase for Ansible.

The source code for the project can be found here. There are 3 files listed here:

getucs.yml - YAML file that defines the playbook
getucsinfo - New module that is defined. This file needs to be in "usr/share/ansible"
getUcsProp.py - getucsinfo module uses functions in this library. This file needs to be in PYTHONPATH.The library provides utility functions to get UCS inventory.

Continue reading Ansible for Network Automation – Part 2 →

Ansible for Network automation – Part 1

Ansible, devops, devopsnet, Programming, python

This blog is part of my series on Devops for Networking. Ansible is a very popular Devops tool and serves similar purposes as Puppet, Chef etc. Ansible has the unique feature that there is no need to install agent on the device side and this makes it very popular for Network device configuration since Network devices are still predominantly a closed system which does not allow agent installation in the device. In this blog, I will cover how to get started with Ansible and in the next blog, I will cover a sample application that I have written.

Ansible basics:

Ansible modules can be run locally or remotely. With the local approach, the module runs locally using apis to talk to remote devices. In remote scenario ,modules are pushed to remote devices, executed as python script and results are returned. Even though there is no need to install remote agent, remote device should allow execution of Python script. Ansible can either be run in command-line for simple tasks or can be executed using a playbook.

Continue reading Ansible for Network automation – Part 1 →

Network device configuration using templates with Jinja2 and YAML

cisco, devops, devopsnet, Jinja2, Programming, python, yaml

This blog is part of my series on Devops for Networking. Typically, Network device configurations for CLI based systems are stored as text files and when its necessary to change parameters like gateway address, vlan, ntp server etc, the script is manually edited and then reapplied to the device. This process is manual and prone to errors. In this blog, I will cover how to automate generation of configuration scripts using Jinja2 and YAML. I will also provide an sample application that I created. For more details, please refer to the references section below.

Tools overview:

Jinja2:

Jinja2 is a Python library for creating configuration based on templates. Jinja2 defines a templating language with which templates are created. The templates can be as simple as a hostname variable that needs to be updated or it can be an array of vlans that needs to be populated. Jinja2 also provides complex templates to cover different scenarios. Following is a very simple example of a template which says ntp_server is a variable that needs to be updated dynamically. We will see later how we can feed in the dynamic values to update.

ntp server {{ ntp_server }}

Continue reading Network device configuration using templates with Jinja2 and YAML →

Cisco device configuration using Netconf

cisco, devopsnet, Netconf, nexus, Programming, xml, Yang

This blog is part of my series on Devops for Networking. In this blog, I will cover how to configure and monitor Cisco NXOS devices using Netconf. In 1 of my earlier blogs, I have provided basics of Netconf and Yang.

I have used Nexus 3k switch for my experiments below.

Netconf has the following layers:

devops8

  • Transport protocol is sshv2.
  • rpc request section contains namespace related details.
  • Operations section could be different operations like edit-config, get-config, commit, lock etc.
  • Content section contains the actual device operation in XML format. The schema for the content can either be specified in XSD format or using Yang. Cisco NXOS devices support XSD format and I will use it in this blog.

Continue reading Cisco device configuration using Netconf →

Cisco device configuration using OnePK

cisco, devops, nexus, onepk, Programming, python

This blog is part of my series on Devops for Networking. onePK is Cisco’s attempt to expose a standard set of APIs to configure and monitor across multiple different Cisco devices. Orchestration and automation applications can use these standard APIs to talk to Cisco devices. In this blog, I will cover a brief overview of onePK and how to get started with onePK to write applications on top of it.

OnePK overview:

Following block diagram from Cisco gives different blocks involved in onePK.

devops6

Continue reading Cisco device configuration using OnePK →

Nexus devices CLI parsing using Python, XML and JSON

cisco, devops, json, nexus, paramiko, Programming, python, xml

This blog is part of my series on Devops for Networking. As I indicated in 1 of my earlier blog, majority of Network devices still have CLI as the only means of configuration and monitoring. CLI is not automation friendly because of obvious reasons. In the last few years, Cisco NXOS devices provides CLI output in XML and JSON format. This allows much easier ways to parse the CLI output which aids in automation. In this blog, I will cover some examples of monitoring Cisco NXOS devices using Python interface to interact with the device and get useful information.

Prerequisites:

Continue reading Nexus devices CLI parsing using Python, XML and JSON →

Cisco UCS automation using Python SDK

cisco, devops, Programming, python, UCS, xml

This blog is part of my series on Devops for Networking. In this blog, I will cover a brief overview of UCS management model, management tools and how to automate configuration and monitoring of Cisco UCS using Python SDK. UCS is Cisco’s Unified computing system that provides a tightly integrated compute, networking and storage solution.

UCS Management

Cisco UCS management information model is a hierarchical tree with each node in the tree representing either physical or logical entity. The node is referred to as MO(Managed object). Physical entities could be chassis, servers, switches and logical entities could be policies, service profiles etc. XML based interface is provided to set and get managed objects. Following picture shows a sample Management tree with Chassis, blades and adapters.

Continue reading Cisco UCS automation using Python SDK →

Policy based forwarding application

Opendaylight, Programming, python

In this blog, I will cover a policy based forwarding application that I wrote in Python.

Use case:

There are many scenarios where regular routing decisions do not suffice and customers want more fine grained control over paths their traffic takes. This could be because of security reasons, better link utilization, vpn concerns etc. Following scenarios are covered in the application.

  • Traffic type(Either cos based or L4 based)
  • Time of the day
  • Bandwidth based

Continue reading Policy based forwarding application →

MuxDemux ODL application

Opendaylight, Programming

Here, I will cover a simple ODL application that does multiplexing and demultiplexing of packet based on incoming vlan.

Use case for the application:

Test generator ports are always a premium because of the high cost associated with it. In our lab, we connect test generator to a switch and the switch is connected to all DUT. The advantage with this scheme is we can use low speed testgen ports(1G test ports are lot cheaper than 10G, 40G) and there is less need for recabling. There is a need to reprogram the switch based on which DUT we need the testgen port to be connected to and this application is a first step towards automating that process.

Continue reading MuxDemux ODL application →