Almost every student who sits down with our counsellors asks some version of the same question.

  • “Mujhe toh networking mein jaana hai, coding kyun seekhun?”
  • “Python toh data science walon ka kaam hai.”
  • “C aur C++ kar liya, ab Python alag se kyun?”
  • “AI hi code likh dega na?”

They're fair questions. And the honest answer is this: you may never have “Python Developer” printed on your visiting card. But open a job description for a network engineer, a security analyst, a cloud or DevOps engineer, a data analyst or an AI engineer today, and there's a good chance it asks for Python, or for the things people do with it: automation, scripting, APIs and handling data.

That's why we stopped describing Python as “one more language” years ago. It's closer to a skill, like typing or spreadsheets once were, that makes everything else you do in IT faster.

Python is in jobs that don't have Python in the title

Python has quietly become the glue of IT work. It connects your real job to the computer, so that the boring, repetitive part gets done by a script instead of by you. The pattern looks like this:

  • Networking+ Python=network automation
  • Cybersecurity+ Python=security automation
  • Cloud+ Python=cloud automation
  • DevOps+ Python=pipeline automation
  • Data+ Python=analytics
  • Statistics+ Python=data science
  • AI and ML+ Python=intelligent applications
  • Development+ Python=web apps and APIs
  • Testing+ Python=test automation
  • Databases+ Python=automated reporting
  • Excel+ Python=pandas and charts inside your spreadsheet, with =PY

Python is a career multiplier. It doesn't have to be your job title.

The one idea to take from this article

Notice what sits on the left of every line: a field you already want to work in. Python doesn't replace it. A network engineer who can script configures a hundred switches in the time it takes a colleague to do three. A data analyst who knows pandas stops copying numbers between spreadsheets every Monday. In both cases, the domain knowledge is what gets you hired, and Python is what makes you the person people want on their team.

Find your role: what Python actually does in it

Pick the role you're aiming for. Each card shows what Python is used for, a real task you'd automate, the tools you'll meet, and where to learn the field itself.

Network administrator or network engineer

What Python does
Configures and backs up many devices at once over SSH and APIs, checks interface and link status, and builds inventory and compliance reports.
A real task
Log in to 100 switches, save their running configurations and flag every one that's still on an old software version, in minutes instead of a day of manual logins.
Tools you'll meet
Netmiko NAPALM Paramiko Ansible (Ansible is itself written in Python)
Learn the field
CCNA course in Nagpur: get the networking right first, then automate it.

Eleven very different jobs, one shared tool. That's the real reason to learn Python: whichever of these you end up in, and many people move between two or three of them over a career, Python comes with you.

Python has arrived inside Excel

Saurabh Joshi

Contributed by Saurabh Joshi
CTO & FDE, Unisoft Technologies · Microsoft Excel Expert

And it isn't only IT jobs. The place where most of the world's data actually lives, the humble spreadsheet, now speaks Python too.

Python as a function, =PY, isn't coming to Excel. It has already arrived in Excel 365. So even spreadsheet users can take advantage of this wonderful language.

Saurabh Joshi, CTO & FDE, Unisoft Technologies

In Excel for Microsoft 365, you type =PY in a cell, or choose Formulas › Insert Python, and the cell becomes a PY Python cell. The code runs in Microsoft's cloud, so there's nothing to install, and the data libraries this article keeps mentioning come ready to use: pandas, NumPy, Matplotlib, seaborn and statsmodels, from Anaconda. A function called xl() reads your cells and tables straight into Python. (Microsoft)

F2PYa Python celltype =PY, then write

# read the Excel table "Sales" into a pandas DataFrame
sales = xl("Sales[#All]", headers=True)

# total sales for each region, returned to the sheet
sales.groupby("Region")["Amount"].sum()

H2PYthe next cell: a chart

sns.barplot(data=sales, x="Region", y="Amount")

The result: a region-wise summary and a bar chart, right in the workbook. No VBA, no pivot-table gymnastics, and no Python installed on the computer.

Think about who that helps. Commerce graduates, accountants, MIS executives and analysts who already live in Excel can now do what formulas struggle with: clean a 50,000-row export, combine sheets, summarise by any column, run a regression, or draw a chart a manager can read, without ever leaving the spreadsheet. If you've been told “Python isn't for you, you're not from IT”, this is your way in. You start with data you already understand.

Can you use it? Python in Excel is generally available on Microsoft 365 business and enterprise plans, in Excel for Windows, Excel on the web and Excel for Mac, and in preview for Family and Personal plans. It isn't available on phones or the iPad. Standard compute is included with the subscription; heavier work can use premium compute, which comes with a limited monthly allowance or a paid add-on. (Microsoft)

Our advice for Excel users is to learn both sides properly: Excel itself first, then Python's fundamentals and pandas. The =PY cells only make sense once you know what a DataFrame is and what Excel already does well. That's the route through our Advanced Excel course and our Python course, which covers pandas and data analysis in depth.

Why Python, and not another language?

Partly because it's popular, and popularity matters more than it sounds: it decides how many libraries, tutorials, answers and jobs exist for a language. Here's where things stand.

Source: TIOBE index, September 2026. TIOBE measures how much a language is searched for and discussed, not how many jobs it has.

Python has been at the top of that list for years. Its share is lower than a year ago, but it's still well ahead of C in second place. Developers tell the same story. In Stack Overflow's 2025 survey of developers worldwide, Python's use jumped by seven percentage points in a single year, which the survey put down to its role as the go-to language for AI, data science and back-end work. (Stack Overflow, 2025)

Popularity alone isn't a reason, though. These are the reasons that matter for a student:

  • It reads close to plain English. You spend your energy on the problem instead of on brackets and declarations, which is why it's such a common first language.
  • Someone has already built the hard part. There's a library for almost everything, from talking to a Cisco switch to training a neural network, and it's free to use.
  • It runs everywhere. Windows, Linux, macOS, servers and the cloud, with the same code.
  • It's the default for AI and data. The major machine learning tools, including PyTorch, TensorFlow and scikit-learn, are used mainly from Python.

To be fair to the other languages: Python isn't the best at everything. JavaScript runs the browser, C and C++ run where speed and hardware control matter, and Java still dominates big enterprise back ends and campus hiring at IT services companies. If that's your target, read Java vs Python for freshers before you choose. Python's strength is breadth: no other language is used in so many different IT jobs.

Logic first, syntax second

This is the part most Python courses get wrong. It's also the heart of how Raina Nair, our lead Python faculty, teaches at Unisoft, whether the class is Python fundamentals, machine learning or deep learning.

Learning Python shouldn't mean memorising syntax. The real goal is to think logically and solve problems.

Raina Nair, Lead Python Faculty, Unisoft Technologies

Many of our students meet that kind of thinking through C, then C++, then data structures. That path isn't wasted time before Python. It's what makes Python make sense:

  • C teaches you what the computer is actually doing: variables and data types, conditions, loops, functions, arrays, and pointers and memory.
  • C++ adds object-oriented programming: classes, objects and inheritance, the way large programs are organised.
  • Data structures and algorithms teach you to break a problem into steps and choose the right way to store and search data. That's the skill technical interviews test, in any language.
  • Python then gives you a far more productive place to apply all of that to real IT problems.

That's why, in Raina's batches, a new topic starts on the whiteboard. Students work the logic out by hand before they write a single line of code, and only then turn it into Python.

Look at the two programs at the top of this page again. The logic is identical: open the log, read it line by line, check each line, count the matches. C makes you manage the details yourself. Python lets you spend that effort on the problem. Once you can think the logic through, the language is the easy part.

So try this before you scroll any further.

The problem: which IP addresses keep failing to log in?

# auth.log has thousands of lines like these:
10:14:07 FAILED login for admin from 10.0.4.17
10:14:09 FAILED login for admin from 10.0.4.17
10:15:31 OK     login for priya from 10.0.2.8
# Which IP addresses failed more than 5 times?

The logic, before any code:

  1. Read the log one line at a time.
  2. If the line contains FAILED, take the IP address (the last word).
  3. Add 1 to that IP's count in a table.
  4. At the end, print every IP whose count is more than 5.

In C, step 3 means building that counting table yourself, as an array of structures or a hash table. That's exactly what a data structures course teaches you, and it's why the Python version below makes sense to you instead of looking like magic.

The same four steps in Python

from collections import Counter

failed = Counter()
with open("auth.log") as log:
    for line in log:                  # step 1
        if "FAILED" in line:
            ip = line.split()[-1]      # step 2
            failed[ip] += 1            # step 3

for ip, count in failed.most_common():
    if count > 5:                  # step 4
        print(ip, count)

That small script is a real security task. Change the file and the condition, and it becomes a network report, a sales summary or a test-result checker. This is why the question employers ask has changed. It's no longer just:

“Do you know Python?”

It's: “Can you use Python to solve an IT problem?”

  • Can you push the same configuration change to 100 network devices?
  • Can you find the suspicious IPs in thousands of security log lines?
  • Can you clean and analyse a large, messy dataset?
  • Can you build a small API that another team can use?
  • Can you automate a deployment step you repeat every day?
  • Can you prepare data for an AI model?

None of those questions is about syntax. Every one of them is about logic.

A roadmap from basics to advanced

Here's the order we recommend, with a simple test at each stage so you know when you're ready to move on. Don't skip ahead: most students who get stuck in advanced Python are really stuck on the basics.

  1. Logic and the basicsVariables, data types, conditions, loops and functions. Solve small problems every day: a marks calculator, a prime-number checker, a simple ATM menu.You're ready when you can solve a small problem without copying a solution.
  2. Python's data structuresLists, tuples, sets, dictionaries and strings, and when to use each one.You're ready when you can choose the right structure for a problem and explain why.
  3. Functions, modules, files and errorsWriting reusable functions, organising code into modules, handling errors properly, and reading and writing text, CSV and JSON files.You're ready when your script survives a missing file or bad data without crashing.
  4. Object-oriented, clean codeClasses and objects, plus the working habits of a developer: virtual environments, installing packages, and Git and GitHub.You're ready when someone else can read your code and run it on their machine.
  5. Advanced PythonComprehensions, generators, decorators, regular expressions, calling web APIs and writing tests.You're ready when you can automate a real task end to end and prove it works with tests.
  6. Your directionThe libraries of your field, from the role cards above, and two or three projects you can explain line by line in an interview.You're ready when your GitHub shows work an employer in your field would recognise.

The trap to avoid: jumping straight to stage 6 because a library looks exciting. A student who “knows pandas” but can't write a loop without help is usually found out in the first technical round.

If your direction is AIThe AI path at Unisoft, led by Raina Nair

  1. Python fundamentals
  2. NumPy & pandas
  3. Statistics & visualisation
  4. Machine learning
  5. Deep learning
  6. AI applications

Stage 6 is a whole journey of its own when you're heading for AI. Raina Nair, our lead Python faculty, teaches it from end to end: from your first Python class, through machine learning, to deep learning and AI. Each step uses the one before it, which is why no step can be skipped.

How we teach this path in Nagpur: logic through our C, C++ and data structures courses, or the Foundation Program straight after 12th. Then our Python course in Nagpur (core, advanced and analytics), whose 12 modules run from programming fundamentals and data structures through functions, files, NumPy, pandas, data cleaning, analysis, visualisation and SQL to a capstone project. Then your direction, from data analytics and AI to DevOps, networking and cybersecurity.

How to practise without wasting months

Courses give you structure. Practice gives you skill. The students who become good at Python aren't always the cleverest in the batch. They're the ones who write code every day.

  • 30 to 45 minutes a day beats a four-hour weekend session. Programming is a habit more than a subject.
  • Type every example yourself. Copy-pasting code teaches your clipboard, not your brain.
  • Automate something in your own life. Rename a folder of photos, total your monthly expenses from a CSV, or remind yourself of assignment deadlines. Real problems teach faster than exercises.
  • Already using Excel at work or college? If you have Microsoft 365, try =PY on a sheet you use every week. Python on your own data teaches faster than any textbook exercise.
  • Read other people's code. Ask the trainer for a well-written solution and work out why each line is there.
  • Use AI as a reviewer, not a writer. Write your own attempt first, then ask an AI tool to review it. We explain why this matters in Will AI replace data analysts?

A prompt that works well for learners: “Don't fix my code. Tell me which line is wrong and give me a hint.”

A note from your trainers

We have taught programming in Nagpur long enough to watch technologies come and go. Languages rise and fall in the rankings, tools change every few years, and today AI can write code that looked like magic not long ago.

What has never gone out of date is a student who can look at a problem, break it into steps, and turn those steps into something that works. That's what we try to build in every batch, whether the class is C, data structures or Python.

We believe programming shouldn't be taught as a collection of commands to memorise. It should build logical thinking, problem-solving and the habit of applying both to real work. Because the technology will change. The ability to understand a problem and build the solution stays with you.

So don't learn Python just because it's popular. Learn it because your IT career, whichever one you choose, is going to need it. Learn Python. Build logic. Automate the boring work. Solve real problems.

Pratigya Thakur & Raina NairFounder & CEO, and Lead Python Faculty, Unisoft Technologies, Nagpur

What a good Python course should give you, and what only you can give

Whichever institute you choose, including us, a course is a partnership. Neither side can do the other's half.

What a good course should give you

  • Logic before syntax, from day one
  • Hands-on practice in every class, not just slides
  • Projects on real, messy data that you can explain
  • Trainers who answer doubts in class, not by email next week
  • Help with your resume, GitHub and mock interviews

What only you can give

  • Daily practice, even 30 minutes
  • Writing the code yourself before asking AI
  • Finishing projects, not just starting them
  • Asking when you're lost, instead of scrolling
  • Showing up, especially on tired days

Ask any institute you're considering how they cover the left column. And be honest with yourself about the right one.

Start Python the right way

Tell us your background and the role you're aiming for, and we'll tell you where to begin: logic first, Python straight away, or a course that combines both. Ask for a free demo class or a free counselling session before you decide anything.

Chat on WhatsApp Call +91 95030 05060

Or see what's inside our Python course in Nagpur.

Unisoft Technologies, Dharampeth, Nagpur. Training students since 2000, with 80,000+ trained and a 4.6★ Google rating. Weekday, weekend and fast-track batches, in the classroom or live online. Email: mail@unisoftindia.org

Questions students ask us

Is Python worth learning in 2026?

Yes, for almost any IT career. Python is first on the TIOBE index for September 2026 at 17.76%, well ahead of C at 10.28%, and in Stack Overflow's 2025 survey 57.9% of developers and 71.8% of people learning to code used it. More importantly, network, security, cloud, DevOps, data, AI and testing jobs all use Python for automation and data work, so it adds to whatever career you choose.

Do I need Python for networking or cybersecurity jobs?

Not on your first day, but it quickly becomes the difference between doing a task by hand and automating it. Network engineers use Python libraries such as Netmiko and NAPALM to configure and back up many devices at once, and security analysts use it to search logs, automate alert checks and write small tools. Learn your core field first, then add Python to it.

Should I learn C before Python?

It isn't required, but the logic it teaches is. C and C++ make you understand variables, loops, functions, memory and objects, and data structures teach you to solve problems step by step. If you already know C or C++, Python takes weeks, not months. If you're starting from zero, begin Python with a course that teaches logic first instead of just syntax.

Can I learn Python from a non-IT or commerce background?

Yes. Python reads more like plain English than most languages, which makes it a good first language. Start with logic and the fundamentals, practise a little every day, and choose a direction such as data analytics, where business sense from a commerce background is an advantage. Our Python course starts from the fundamentals.

Can I use Python inside Excel?

Yes. In Excel for Microsoft 365 you can type =PY in a cell, or choose Formulas › Insert Python, and write Python directly in the spreadsheet. The code runs in Microsoft's cloud, so nothing needs to be installed, and pandas, NumPy, Matplotlib, seaborn and statsmodels are ready to use. The xl() function reads your cells and tables into Python. It is generally available for Microsoft 365 business and enterprise plans in Excel for Windows, the web and Mac, and in preview for Family and Personal plans; it is not available on phones or the iPad.

How long does it take to learn Python from basics to advanced?

It depends mostly on how much you practise. Our Python course (core, advanced and analytics) typically runs 3 to 4 months, with weekday, weekend and fast-track batches. Becoming job-ready in a specific direction, such as data science or DevOps, takes longer because you also learn that field's tools.

Which Python libraries should I learn first?

None, until your fundamentals are solid. After that, follow your direction: pandas, NumPy and Matplotlib for data analysis; scikit-learn and PyTorch for machine learning; Netmiko and NAPALM for networking; boto3 for AWS; Django, Flask or FastAPI for web back ends; pytest and Selenium for testing.

If AI can write Python code, why should I learn it?

Because you still have to read, check and fix what AI writes, and interviews test whether you can solve problems yourself. AI-generated code often looks correct and still has mistakes that only someone who understands Python will spot. Learn the language, then use AI to work faster. We go deeper in Will AI replace data analysts?

Who teaches Python at Unisoft Technologies?

Python at Unisoft is led by Raina Nair, our lead Python faculty, who has been teaching since 2017. Raina teaches Python from the fundamentals to advanced level, and the subjects it leads into: machine learning, artificial intelligence and deep learning. Raina also teaches C, C++ and Java, and is an Oracle Certified Instructor with OCP and OCA certifications in Java and Oracle Database.

Where can I learn Python in Nagpur?

Unisoft Technologies in Dharampeth, Nagpur, has taught IT since 2000. Our Python course covers 12 modules from fundamentals to a capstone project, with classroom and live online batches. You can ask for a free demo class or a free counselling session on +91 95030 05060.

About the authors

Raina Nair, Lead Python Faculty at Unisoft Technologies, Nagpur

Raina Nair

Lead Python Faculty, Unisoft Technologies · Python, machine learning, AI and deep learning · 9+ years

Raina leads Python teaching at Unisoft Technologies and teaches the subjects Python leads into: machine learning, artificial intelligence and deep learning. Raina also teaches programming from the ground up, from C and C++ fundamentals and object-oriented programming to Java full stack, with a whiteboard-first approach: students work the logic out on the board before they write a single line of code. That idea is at the heart of this article.

Teaches

  • Python
  • Machine learning
  • AI
  • Deep learning
  • C & C++
  • Java
  • Oracle Certified Instructor
  • OCP Java
  • OCA Java
  • OCP DBA
  • OCA DBA
LinkedIn Verified certifications
Pratigya Thakur, Founder & CEO of Unisoft Technologies, Nagpur

Pratigya Thakur

Founder & CEO, Unisoft Technologies, Nagpur · in IT training since 2000

Pratigya founded Unisoft Technologies in Dharampeth, Nagpur, in September 2000. The institute has since trained more than 80,000 students in programming, databases, networking and data analytics. An Oracle Certified Professional DBA and Red Hat Certified Engineer, Pratigya also co-founded The Pride School in 2008 and founded NS Mentors in 2022.

  • Oracle OCP DBA
  • Oracle OCP Advanced PL/SQL
  • Red Hat RHCE
LinkedIn
Saurabh Joshi, CTO and FDE of Unisoft Technologies, Nagpur

Saurabh Joshi

CTO & FDE, Unisoft Technologies · contributed the section on Python in Excel

Saurabh leads technology at Unisoft Technologies and is its forward deployed engineer, building and running the institute's own data and web systems with the people who use them. With 16+ years in databases, analytics and web technologies, he teaches SQL, PL/SQL, Oracle DBA, Advanced Excel and Tableau, which is why Python arriving inside Excel matters so much to the students he teaches.

  • OCP DBA
  • OCA DBA
  • Oracle SQL Associate
  • Excel Expert (MO-211)
  • Excel Associate (MO-210)
Full profile LinkedIn Verified certifications

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Sources

  1. TIOBE Software, TIOBE Programming Community Index, September 2026. https://www.tiobe.com/tiobe-index/
  2. Stack Overflow, 2025 Developer Survey: Technology, “Programming, scripting, and markup languages”. https://survey.stackoverflow.co/2025/technology
  3. Microsoft Support, Introduction to Python in Excel. https://support.microsoft.com/en-us/office/introduction-to-python-in-excel-55643c2e-ff56-4168-b1ce-9428c8308545
  4. Microsoft Support, Python in Excel availability (checked 2 October 2026). https://support.microsoft.com/en-us/office/python-in-excel-availability-781383e6-86b9-4156-84fb-93e786f7cab0