4.8 LPAHyderabadAnkit Singh
Data Analyst
- Placed at
- FINELABS
- Program
- Data Analytics Batch
- Batch
- DA/09/0823/S WD 7PM
Choose the best training program according to your career.
Improve the performance of your business with our innovative Industrial Training Program.
Read More →
Our instructor-led training classes are designed to make you an expert.
Read More →
Real-life case studies are a great way to demonstrate your practical knowledge.
Read More →
Explore blogs, latest technologies and industry updates with practical examples.
Read More →Browse all available training programs and choose the right one for your career.
Read More →Know more about who we are and what we stand for.
Discover our mission to equip individuals with essential IT skills and industry expertise.
Read More →Learn, practice and plan your career — bilkul free.
Book a free video counselling session and pick the right course for you.
Read More →Kurnool — once the first capital of Andhra State — now sits beside one of the world's largest solar parks, a growing cement belt, a major seed industry and the groundnut and cotton fields of western Rayalaseema. Sunlight, limestone and soil are its resources; data is fast becoming another. Panel output, kiln readings, seed germination rates and mandi prices all need people who can interpret them. Uncodemy's Data Analytics Course trains Kurnool learners for that work through 6–7 months of live online classes in Excel, SQL, Python, Statistics, Power BI, Tableau and Generative AI.
There is no Uncodemy centre in Rayalaseema's gateway city. The institute's two classrooms are in Noida and in Delhi's Shakarpur Extension, where the building stands beside DSEU Ambedkar College and near the Nirman Vihar and Laxmi Nagar Metro Stations. Kurnool learners are seated in those batches virtually and get 120-plus learning hours, more than 75 trainer-led classes, practical assignments and a placement mentor. Course fee: ₹17,500, which with 18% GST becomes ₹20,650.
Picture the six to seven months as commissioning a new solar block: Excel and SQL are the mounting structures, Python and statistics the wiring, and Power BI, Tableau and Gen AI the inverters that turn raw data into usable output — all taught live online. Practice files come from solar parks, kilns, seed plants and mandis, a mentor inspects each stage, and the final weeks are your performance test: mock interviews.
Graduates leave able to take an inverter log, a kiln shift sheet or a seed-lot germination register and turn it into a clean, analysed and well-reasoned report using whichever tool fits. Eligible graduates move on to analyst applications after career preparation; selected outcomes are listed below.
4.8 LPAHyderabadData Analyst
4.8 LPAIndiaData Analyst
4.0 LPADelhiData Analyst
3.25 LPAPuneData Analyst
3.0 LPANoidaData Analyst
3.0 LPADelhiData Analyst
Location badges show where each learner was placed. Kurnool learners join these same live online batches and the same career-preparation process; outcomes depend on individual effort and the job market.
A solar park produces a reading every few minutes from thousands of inverters; a cement kiln logs temperature, fuel and clinker output every shift; a seed company tests germination for every lot it ships. Left alone, those figures say little. Data analytics brings them into focus — cleaning the records, testing what they reveal with statistics and showing the outcome as charts that explain where power is lost, why quality varies or which lots to recall. Hospitals, banks and traders in Kurnool use the same method for their own questions.
In a Kurnool workplace, an analyst may query SCADA exports or ERP tables using SQL, remove duplicate readings and fill gaps, compare blocks, kilns or seed varieties in Excel or Python, build a
Power BI or Tableau dashboard and then discuss results with a plant engineer, production head, quality manager or agri-trader.
Consider a solar power plant. Analytics explains why output dipped last April; data science forecasts generation for the coming month; business analytics recommends cleaning cycles, maintenance windows and grid-scheduling strategy.
| Aspect | Data Analytics | Data Science | Business Analytics |
|---|---|---|---|
| Core question | What happened, and why? | What will happen next? | What should the business do? |
| Coding depth | Low to moderate | High | Low |
| Typical entry salary | ₹3–6 LPA | ₹8–18 LPA | ₹4–7 LPA |
| Time to job-ready | 6–7 months | 9–12 months | 5–6 months |
Starting salaries listed are rough brackets from the cited sources; like a plant's capacity utilisation, the real figure varies with employer, role, skill, experience and season.
Course rating: 6–7 months, 75-plus live online lectures, over 120 learning hours. Installation order: Excel and SQL; then Python, statistics, cleaning and exploratory work; then Power BI, Tableau and Generative AI. Solar, cement and seed datasets feature throughout, a guided build closes each phase, and your capstone is the flagship array of your portfolio.
Eligibility: A completed bachelor's degree in any subject is needed (the eligibility criteria page lists specifics). We introduce SQL and Python from absolute zero, so earlier coding isn't required. Basic numeracy helps, and the statistics module rebuilds core concepts. A laptop with 8GB RAM and dependable internet is advised for lab sessions.
Weekday and weekend live batches are available, timed so college students, plant shift staff and office employees in Kurnool can each attend. A free online demo class can be booked before enrolment.
Seats are limited and updated daily. All timings are in IST.
Across nine modules and 120-plus hours, lessons trace a real analysis from sunrise to sunset — capturing readings, filtering noise, analysing, interpreting, charting and reporting to the site head. Each module closes with a marked practical on authentic data, and module nine assembles your portfolio.
| Module | Topic | Hours | Tools |
|---|---|---|---|
| 1 | Excel for Data Analytics | 12 | Excel, Power Query |
| 2 | SQL & Database Management | 18 | MySQL |
| 3 | Python for Data Analytics | 20 | Python, Pandas, NumPy |
| 4 | Statistics & Business Mathematics | 12 | Excel, Python |
| 5 | Data Cleaning & EDA | 12 | Python, Pandas |
| 6 | Power BI | 18 | Power BI Desktop |
| 7 | Tableau | 10 | Tableau Public |
| 8 | AI & Gen AI for Analysts | 8 | ChatGPT, Copilot |
| 9 | Capstone & Career Prep | 10 | All tools |
| Total | 120 Hours | 10+ tools |
Irshad Khan — Senior Trainer, 8+ Years Experience. Specialization: Data Science, Data Analytics, Business Analyst, SQL, Power BI, Python, Generative AI, Agentic AI.
Once every module, assignment and the capstone clear inspection, Uncodemy issues your Data Analytics Program Certificate — showing course name, months of study, tools learned, completion date and a lookup code that works like an asset tag.
Solar developers, cement producers and seed companies prefer evidence to promises, so the certificate is supported by graded spreadsheet, SQL, Python, statistics, BI and Gen AI work and a capstone that solves a complete business problem.
Whether a solar developer, a cement producer or a Hyderabad firm, any recruiter can confirm a Kurnool learner's credential on Uncodemy's portal within moments.
Uncodemy Certificate Verification — Online Certificate Verification & Download: certificate.uncodemy.com
_3.webp)
_2.webp)
Uncodemy is managed by Uncodemy Edutech Pvt. Ltd., and each of its programmes is designed with employment as the goal. Classroom groups meet in Delhi and Noida, and live online groups extend identical instruction to Kurnool and all parts of India. Learners include beginners, graduates, freshers and serving professionals.
Inside the course, spreadsheets, SQL, Python, statistics, Power BI, Tableau and Gen AI are applied to genuine datasets as projects — the same work an analyst does at a solar O&M desk, a cement plant's process office, a seed company's QA lab or a Kurnool hospital's records section. The module list is published before you enrol.
Teaching is reinforced by mentor sessions, graded exercises, project reviews, mock interviews and career guidance. The career support policy, issued in writing before enrolment, explains the help on offer, its limits and who qualifies.
Learners in Kurnool who are interested in AI, Machine Learning, Data Science or Business Analysis may enrol in those live online programmes with Uncodemy.
Switch on from Kurnool: stream live lectures, practise on generation, kiln and seed data, assemble a portfolio and connect with analyst roles in Rayalaseema, Hyderabad, Bengaluru or remote teams.
Kurnool district hosts one of the largest solar parks anywhere, alongside wind farms and transmission infrastructure that generate continuous performance data. Developers, operations-and-maintenance contractors and grid operators need analysts to track generation, soiling losses, inverter faults and availability. The limestone belt around Nandyal and Banaganapalle supports several large cement plants with their own production, energy and logistics reporting.
The district is also a seed hub: hybrid cotton, chilli and vegetable seed companies process and test lots here, while groundnut, cotton and onion trading through Kurnool and Adoni markets generates arrivals and pricing data. Hospitals, banks, government departments and educational institutions add further demand for MIS and analytics skills.
Hyderabad and Bengaluru are each a few hours away, and remote analytics roles are common. Across employers, SQL and a BI tool are expected; those who succeed can frame the business question precisely, choose a suitable metric and explain the recommendation clearly in Telugu, Kannada, Hindi or English.
Kurnool graduates generally target Data Analyst, Business Analyst, MIS Executive/Analyst, Business Intelligence Analyst, Marketing/Product Analyst and Operations Analyst vacancies. A solar operator asks why one block under-generates, a cement plant why kiln fuel use crept up, a seed company which lots failed germination — and each answer flows from SQL, spreadsheets and a dashboard.
| Role | Core Tools |
|---|---|
| Data Analyst | SQL, Excel, Python, Power BI |
| Business Analyst | SQL, Excel, BI tools |
| MIS Executive / Analyst | Excel, SQL, Power BI |
| Business Intelligence Analyst | Power BI, Tableau, SQL, DAX |
| Marketing / Product Analyst | SQL, Python, BI tools |
| Operations Analyst | Excel, SQL, Power BI |
Kurnool freshers generally enter as Data, MIS or Business Analysts and progress within two to four years into BI, energy, production, supply-chain or operations analytics, on the strength of complete analyses and a growing grasp of their sector.
An analyst's earnings depend on experience, sector and practical command of SQL and BI, and pay for the same designation can vary considerably. Profiles limited to charts tend to begin lower; those who can also write efficient queries, structure problems and argue a reasoned recommendation begin higher and move ahead faster.
| Career Level / Role | Indicative Salary Range |
|---|---|
| Entry-Level Data Analyst | ₹3–6 LPA |
| Data Analyst (Mid-Level) | ₹6–10 LPA |
| Senior Data Analyst | ₹10–15 LPA |
| Business Intelligence Analyst | ₹7–12 LPA |
Sources reviewed: AmbitionBox, Glassdoor, Indeed and Uncodemy placement records. Reviewed: 12 October 2026.
Solar developers and large cement groups commonly pay around mid-bracket; traders and smaller local firms may open lower; Hyderabad, Bengaluru and work-from-home roles can go higher. These are illustrative figures that shift with role, ability, experience, city, employer and market — Uncodemy assures neither pay nor placement.
Uncodemy's hiring network includes more than 850 companies across India. For Kurnool learners, analyst opportunities concentrate in:
Solar and wind energy — generation, soiling-loss, inverter-fault and availability analytics
Cement and limestone — kiln performance, energy, quality and dispatch reporting
Seeds and agri-trade — lot germination, processing yield, groundnut and cotton price tracking
Healthcare, banking and public administration — patient-flow, credit and scheme dashboards
Hyderabad and Bengaluru offices or work-from-home teams — analytics openings beyond the Tungabhadra
A solar O&M contractor, a cement works and a seed processor will each test different strengths, so decide early which you want and wire your portfolio accordingly.
Analytical skill accumulates the way a solar array does — panel by panel, each one adding to the output. Leave gaps and the system underperforms, usually exposed in a technical interview or the first months on the job.
Excel proficiency — XLOOKUP, pivot tables and Power Query for block-wise or kiln-wise summaries in minutes.
SQL fluency — joins across readings, assets and maintenance logs, grouped totals, subqueries and window functions.
Python capability — load months of minute-level inverter data into Pandas, crunch it with NumPy and let a script produce the daily generation report automatically.
Statistical reasoning — sampling, hypothesis testing and regression so generation or quality conclusions can be defended.
BI delivery — Power BI with DAX or Tableau with calculated fields, tuned until a site manager can spot an underperforming string on the dashboard at a glance.
A Rayalaseema portfolio — three to five projects, such as soiling-loss analysis or seed-lot quality trends, each ending in a recommendation.
Interview preparation — timed SQL practice, case rehearsal and a CV and LinkedIn that quantify outcomes.
Most Kurnool learners reach interview standard after six to seven months of steady study; regular daily practice yields more than intermittent long sessions.
Kurnool learners can choose from many analytics courses at markedly different prices, most based in Hyderabad or Bengaluru. The summary below lists what this programme provides.
| Factor | This Program |
|---|---|
| Duration | 6–7 months |
| Learning hours | 120+ hours |
| Tools covered | 10+ tools |
| Gen AI module | Dedicated 8-hour module |
| Projects | 5 guided + 1 capstone |
| Career support | Resume, LinkedIn, mock interviews, hiring network |
Six to seven months and ten-plus tools may look like oversizing, but a junior at a solar park or cement plant is regularly asked to clean data in Excel, pull it with SQL, automate in Python and present on a dashboard. Recorded courses cost less, and someone needing only an Excel and Power BI refresh could choose one.
Format doesn't change the syllabus, trainers, projects or fee, so choose by convenience. From Kurnool, live online classes are the obvious fit — lectures streamed in real time to your home, doubts cleared immediately and timings that bend around plant shifts, college or field visits.
Uncodemy's physical classrooms are roughly 1,600 km north in Noida and Delhi's Shakarpur area, which rules out hybrid study for Rayalaseema. Remote learners keep every entitlement — live lessons, recordings, doubt clinics and the complete placement service — and an approved change of format carries progress across.
| If you want... | Recommend |
|---|---|
| Only Excel + Power BI basics | A shorter course may be sufficient |
| Full analyst career transition | This program |
| Heavy ML/Data Science | Choose Data Science |
| Business-focused analytics | Consider Business Analytics |
| Self-paced learning | Recorded course |
Faculty behind the Kurnool batches. Kurnool learners are taught in real time by trainers who also teach in our Delhi and Noida classrooms — same faculty, same syllabus, delivered live online. Senior Trainer Irshad Khan heads the Data Analytics track and signed off its curriculum.
Uncodemy keeps teaching and checking separate: domain reviewer Upendra Kumar Tiwari verifies the content without teaching the batch. In doubt-clearing sessions, trainers often rework examples around cement and limestone and seeds and agri-trade — the kind of data employers in Kurnool & Rayalaseema actually hold.
All trainers and reviewers are published on the Uncodemy trainers page with their domain and experience.

Senior Data Science Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.

Data Analytics & AI Trainer
Expertise8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.

Data Analytics & AI Trainer
Expertise7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.

Data Analytics Trainer
Expertise5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.

Data Analytics Trainer
ExpertiseTrainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.

Data Analytics Trainer
Expertise3+ years building generative AI and machine learning systems, now Senior Gen AI Engineer at Uncodemy, with deep work in RAG, knowledge graphs, data analysis and AWS.
NEMI, an enterprise memory system built on RAG, knowledge graphs and vector databases, plus automated web-scraping bots and generative AI chatbots and predictive analytics for startups.

Data Analytics Trainer
Expertise14+ years in banking and insurance operations at Aon Hewitt, NIIT Technologies and Coforge, now teaching Excel, SQL, Python and Power BI through real business scenarios.
MIS reports and Excel dashboards for leadership tracking SLAs, error rates and backlog, SQL data cleaning and validation across systems, and live Power BI dashboards.

Data Analytics Trainer
Expertise5+ years across roles at Concentrix, Amazon and Tech Mahindra. A certified Data Scientist who now teaches data science and analytics as Academic Faculty at Uncodemy.
Credit risk management analytics at Tech Mahindra, business communications analytics, and chatbot solutions built with prompt engineering and machine learning.

MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.

CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Kurnool batches last six to seven months and include more than 75 live online classes amounting to over 120 hours; learners choose weekday or weekend timings to suit plant shifts or college.
Programming experience is not assumed. Graduates from commerce, agriculture or arts streams in Kurnool begin SQL with a basic SELECT and Python with simple variables, while the first two months concentrate on Excel and SQL.
Your toolkit holds more than ten items: Pandas, NumPy, core Python and SQL for wrangling sensor and sales data; Statistics for inference; Tableau, Power BI and Excel for display; Copilot and ChatGPT to speed routine work.
Module 8 provides eight hours on Generative AI — formulating data questions for an assistant, reviewing the SQL or Python it produces, applying Copilot within Excel and Power BI, and identifying unreliable results.
Six projects form the portfolio: five guided studies across retail, banking, HR, e-commerce and healthcare, plus a capstone of the learner's choosing. Solar-generation or seed-lot data would be well suited to Kurnool employers.
Each of the 75-plus classes is delivered live by a trainer, and recordings are made available for revision; one syllabus governs online, classroom and hybrid formats.
For Kurnool learners the total fee is ₹20,650, comprising ₹17,500 and 18% GST; classes, materials, projects, certification and placement support are included, and EMI is available from ₹4,032 a month.
Instalment plans begin at ₹4,032 monthly, with tenure and approval determined by the financing partner and arranged through a counsellor.
A complimentary live demo may be attended from Kurnool to observe instruction, put questions to a trainer and review the syllabus before enrolling.
Placement assistance covers CV and LinkedIn revision, portfolio review, mock interviews and openings from more than 850 companies; employers retain the hiring decision, so employment cannot be guaranteed.
Freshers are taken on — by solar O&M contractors, cement plants, seed companies, hospitals and remote analytics teams — when they can prove SQL, a dashboard tool and finished projects. Opening salaries generally sit near ₹3–6 LPA.
Guide numbers: ₹3–6 LPA at the start, ₹6–10 LPA a few years in, ₹10–15 LPA for seniors. Kurnool positions often pay below Hyderabad or Bengaluru for the same title; Uncodemy commits to no figure.
Kurnool alumni usually start as Data, MIS or Business Analysts, then progress into energy, BI, production, supply-chain or operations analytics.
A finished degree in any subject is all that's required; no programming or analytics background is assumed, and Kurnool batches combine college finalists, plant staff and career switchers.
Read them like a plant's projected yield — informative, not guaranteed. They come from our placement records and public review platforms, both updated periodically; actual outcomes depend on skill, background, location, employer and timing, and lenders decide EMIs.
Rayalaseema has no Uncodemy classroom; physical teaching happens only in Delhi and Noida, so Kurnool learners follow identical batches over a live link. When in Delhi, you'll find the Shakarpur Extension office close to Nirman Vihar Metro.
Upward of 850 recruiters — Fiserv, upGrad, Clarivate, HSBC and Genpact among them. Our records show Business Analysts hired by HSBC and Fiserv, a Genpact Process Developer Analyst and a Clarivate Intellectual Property Analyst.
In analyst hiring, a portfolio says more than a certificate. Below are five learner capstones with their mentors and source code; the Kurnool note on each card suggests how to rebuild it around solar and wind energy.
A retail chain's sales records are standardised in SQL Server and presented in Power BI with filters for region, month and category, each chart addressing a stated requirement.
Kurnool version: Run the same SQL Server + Power BI pipeline on solar and wind energy sales from Kurnool and compare months, products and outlets.
Learners create an online music store's PostgreSQL schema in PgAdmin4 from an entity design and query it to find leading genres, recurring customers and growth potential.
Kurnool version: Model a seeds and agri-trade catalogue the same way and rank items, customers and areas of Kurnool & Rayalaseema by revenue.
Learners treat India's COVID-19 record like noisy inverter data — patching gaps in Pandas, computing rates with NumPy and plotting each state's curve in Matplotlib.
Kurnool version: Clean and chart public health or footfall data for Kurnool & Rayalaseema with the same Pandas and Matplotlib workflow.
Python, SQL and Power BI are combined into a monthly generation, revenue and maintenance report for an imaginary solar-park operator.
Kurnool version: Build a scorecard of cement and limestone employers around Kurnool — size, hiring trend and pay bands — with SQL and DAX.
Python | Jupyter Notebook | Power BI | SQL | Mr. Upendra Kumar Tiwari – Senior Data Science Trainer | Pawan Mehra – Data Analyst
Kurnool version: Swap IPL data for solar and wind energy seasonality in Kurnool and show peaks, slumps and outliers in one dashboard.