Home› Courses› Data Science Course

End-to-End Portfolio 📍 Dilsukhnagar, Hyderabad ✅ Completion Terms Apply

Data Science Course

Build an end-to-end data workflow: frame a question, prepare data, analyse patterns, evaluate models and communicate limitations through documented projects.

⏱

DURATION

12 Weeks (typical plan)

🎯

LEVEL

Beginner to Intermediate

💻

MODE

Classroom · Live Online · Hybrid

🏆

CERTIFICATE

On meeting completion requirements

Tools & Technologies You Will Learn

Python SQL Pandas Statistics Scikit-learn Git

Enroll on WhatsApp → View Curriculum

📊

Free Demo Available
Contact us for current batch fees & EMI options

⏱ Duration: 12 Weeks (typical plan)
🎯 Level: Beginner to Intermediate
💻 Classroom · Live Online · Hybrid
🏆 Completion certificate after meeting course requirements
📁 Guided project and portfolio preparation
🧭 Prerequisites explained before enrollment
📞 Current trainer and batch details available before payment

Ask About Enrollment Book Free Demo Class Call: +91 93900 23585

Ask for the current syllabus, trainer, schedule, fees and support terms before enrolling.

About This Course

Build an end-to-end Data Science portfolio

The learning path combines Python and SQL foundations with statistics, data preparation, exploratory analysis, modelling, evaluation and clear communication.

Projects should show the question, data provenance, cleaning decisions, baselines, evaluation, limitations and reproducible work—not only a final accuracy score.

What makes this course different

🔎

Start with the question

Define the decision, target, constraints and success measure before selecting a model.

🧹

Prepare data carefully

Document quality checks, missing values, leakage risk and transformation decisions.

🧪

Evaluate honestly

Use baselines, validation, appropriate metrics and error analysis.

📁

Show reproducible work

Create notebooks, code, documentation and a concise project explanation.

Course Curriculum

8 modules · 12 Weeks (typical plan) · Guided practical work

The sequence below describes the current course plan. Ask for the dated batch syllabus because tools and module order may change.

Python Foundations for Data

9 topics · Weeks 1-2

Python setup

Variables and control flow

Functions

Collections

Files and exceptions

NumPy basics

Pandas basics

Jupyter workflow

Practice dataset

SQL and Data Access

8 topics · Week 3

Relational concepts

SELECT and filtering

Aggregations

Joins

Subqueries and CTEs

Window functions

Data-quality queries

Practice case

Statistics and Experiment Thinking

9 topics · Weeks 4-5

Distributions

Sampling

Summary statistics

Confidence intervals

Hypothesis tests

Correlation and causation

Experiment design basics

Practical interpretation

Case review

Data Preparation and EDA

9 topics · Week 6

Data provenance

Missing values

Duplicates and outliers

Feature types

Leakage prevention

Visualization choices

Exploratory questions

Data-quality report

EDA presentation

Machine Learning Foundations

9 topics · Weeks 7-8

Supervised learning

Regression

Classification

Trees and ensembles

Feature engineering

Pipelines

Train and validation splits

Cross-validation

Baseline project

Model Evaluation and Explanation

8 topics · Week 9

Metric selection

Class imbalance

Thresholds

Error analysis

Feature importance

Interpretability limits

Fairness checks

Evaluation report

Deployment and Reproducibility Basics

7 topics · Week 10

Project structure

Environment files

Version control

Model persistence

Simple API or app

Monitoring concepts

Documentation

Capstone Project

8 topics · Weeks 11-12

Problem framing

Data review

Analysis plan

Baseline

Model and evaluation

Limitations

Repository and README

Presentation and review

Get Full Curriculum on WhatsApp →

Career Relevance

Roles where these skills may be useful

Training does not guarantee a job, salary, promotion or internship. Outcomes depend on prior experience, project quality, assessment performance and employer requirements.

📊

Data Analyst

Data preparation, analysis, reporting and decision-support work.

🧪

Junior Data Scientist

Baseline modelling and evaluation under experienced supervision.

🤖

Machine Learning Learner

A foundation for deeper model, engineering and deployment study.

🏢

Domain Analytics Professional

Apply data methods in finance, healthcare, marketing, HR or operations.

Ask for current career-support terms

We can explain the included resume, portfolio and interview support before enrollment. Employer decisions remain independent.

Who Is This For

This course is designed for you if…

🎓

Students and graduates

Learners willing to build programming, statistics and project foundations.

🔄

Career switchers

People prepared for a structured prerequisite path rather than a shortcut.

💼

Working professionals

Domain specialists who want to analyse data and communicate evidence.

🧑‍💻

Developers and analysts

People adding modelling, evaluation and reproducible data workflows.

Prerequisites

Basic computer use Comfort with school-level mathematics Regular practice time Python starter support available for beginners

FAQs

Questions about Data Science Course?

Not finding your answer? Ask for the current syllabus, prerequisites, trainer, fees and batch schedule.

Ask on WhatsApp →

Do beginners need coding experience?

Beginners can start with the foundation modules, but Data Science requires consistent Python, SQL and statistics practice. Ask whether prerequisite support is included in your batch.

How is project work evaluated?

A useful rubric should cover problem framing, data quality, analysis, model choice, evaluation, reproducibility, limitations and communication. Request the current rubric.

Does the course guarantee a Data Science job?

No. It develops skills and portfolio evidence; hiring depends on your complete profile, project quality, interview performance, experience and employer requirements.

Which tools are included?

The core plan uses Python, SQL, Pandas and Scikit-learn. Request the dated syllabus for exact libraries, platforms and account requirements.

Can I attend online?

Selected batches may be available live online or hybrid. Confirm the trainer, session format, timings and support process for the current batch.

Ready to start?

Review the Data Science Course before you enroll

Book a free demo to review the teaching approach, prerequisites, current trainer, syllabus, schedule, fees and project expectations.

Ask for Current Batch Details → Call: +91 93900 23585

📍 Dilsukhnagar, Hyderabad · Online across India & Internationally · Mon–Sat 9AM–8PM