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INDUSTRY-ALIGNED DATA SCIENCE TRAINING

Advanced Data Science
Certification Program

Data Science Training in Hyderabad

A 6-month Advanced Data Science Certification Program that takes you from mathematics, statistics and Python programming through machine learning, business intelligence and model deployment. Eight hands-on modules and a two-month real-time internship — built to get you job-ready as a data scientist, not just someone who can run a notebook.

Course Duration
6 Months
Structured Learning
4 Months
Industry Internship
2 Months
Course Fees
₹55,000 / ₹60,000
Online / Offline
View Module Roadmap
Advanced Data Science Certification Program skill map — Python, SQL, Jupyter, Data Visualization, Machine Learning, Deep Learning, AWS Cloud, MLOps, Excel, Tableau, Power BI, Big Data
Industry-Aligned
180+ Hrs Hands-On
“
In God we trust; all others must bring data.
— W. Edwards Deming, Statistician

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Data Science Course Curriculum

Eight Modules. One Complete Data Science Skillset.

How can I become a Data Scientist?

Get an Answer
01

Mathematics for Data Science

20 Hrs · 2 Weeks{<Explore Me />}
02

Python Programming

30 Hrs · 3 Weeks{<Explore Me />}
03

Data Wrangling (SQL + Cleaning)

20 Hrs · 2 Weeks{<Explore Me />}
04

Exploratory Data Analysis (EDA)

20 Hrs · 2 Weeks{<Explore Me />}
05

Data Visualization (Matplotlib / Seaborn)

20 Hrs · 2 Weeks{<Explore Me />}
06

Business Intelligence Tools (Power BI / Tableau)

20 Hrs · 2 Weeks{<Explore Me />}
07

Machine Learning Fundamentals

30 Hrs · 3 Weeks{<Explore Me />}
08

Model Deployment

20 Hrs · 2 Weeks{<Explore Me />}
Why This Data Science Course

A Data Science Course Built to Make You Job-Ready, Not Just Certified

Industry-aligned curriculum built around the same tools and workflows used by data teams today

100% hands-on delivery — every module closes with a lab exercise or a real project, not slides

Direct, hands-on time on Power BI and Tableau — the dashboard tools analysts are tested on in interviews

Structured path from mathematical foundations through Python, SQL, machine learning and deployment

Curriculum mapped toward globally recognised certification pathways (Google Data Analytics, IBM Data Science, Power BI and more)

A minimum of five portfolio projects across the program, documented to professional reporting standards

Real-time internship exposure across data analysis, dashboarding and model deployment

Dedicated placement support — resume reviews, mock interviews and a hiring-partner network

Course Duration & Learning Path

Your Data Science Training Timeline, From Math to Deployment

180 hours of core curriculum across eight modules, followed by a two-month real-time industry internship.

01
Mathematics for Data Science
2 Weeks · 20 Hrs
02
Python Programming
3 Weeks · 30 Hrs
03
Data Wrangling (SQL + Cleaning)
2 Weeks · 20 Hrs
04
Exploratory Data Analysis (EDA)
2 Weeks · 20 Hrs
05
Data Visualization (Matplotlib / Seaborn)
2 Weeks · 20 Hrs
06
Business Intelligence Tools (Power BI / Tableau)
2 Weeks · 20 Hrs
07
Machine Learning Fundamentals
3 Weeks · 30 Hrs
08
Model Deployment
2 Weeks · 20 Hrs
C
Capstone
End-to-End Data Science Project
Final Module Project
I
Final Phase
Real-Time Industry Internship
2 Months
Data Science Tools

Python, SQL, Power BI & the Tools You'll Master

The complete toolset used across the program — from mathematical foundations to machine learning, BI dashboards and deployment.

NumPy

Numerical computing library used for array operations and mathematical computation in data science.

SciPy

Scientific computing library used for statistics, optimization and advanced mathematical functions.

Excel

Spreadsheet tool used for quick data analysis, calculations and lightweight reporting.

Google Sheets

Cloud-based spreadsheet tool used for collaborative data analysis and quick calculations.

Python

Core programming language used across every module, from statistics to machine learning.

Jupyter Notebook

Interactive notebook environment used for data exploration, analysis and model prototyping.

Pandas

Data manipulation library used to clean, transform and analyse structured datasets.

VS Code

Primary code editor used for writing, debugging and testing Python and data science code.

SQL

Query language used to extract, filter and aggregate data from relational databases.

MySQL / PostgreSQL

Relational database systems used to store and query structured data.

OpenRefine

Data-cleaning tool used to explore, standardise and transform messy datasets.

Pandas Profiling

Automated data-profiling tool used to generate quick exploratory data analysis reports.

Matplotlib

Core Python plotting library used to build line, bar, scatter and histogram visualizations.

Seaborn

Statistical visualization library built on Matplotlib, used for heatmaps and distribution plots.

Plotly

Interactive charting library used to build explorable, presentation-ready visualizations.

Power BI

Microsoft's business intelligence platform used to build interactive dashboards and reports.

Tableau

Business intelligence platform used to build interactive, drill-down data visualizations.

Scikit-learn

Machine learning library used to build, train and evaluate classical ML models.

Flask

Lightweight Python web framework used to build and deploy REST APIs for ML models.

FastAPI

Modern Python web framework used to build production-grade APIs for serving ML models.

Docker

Containerization platform used to package and deploy data science applications consistently.

Streamlit

Python framework used to build interactive web apps around data science and ML models.

AWS / Azure Basics

Cloud platform fundamentals used to deploy and host data science applications in production.

Data Science Projects

Real Data Science Projects for Your Portfolio

Every module is reinforced with hands-on work — a minimum of five projects across the program, each added to your portfolio and resume.

Capstone

End-to-End Data Science Project

Take a business problem from raw data to a deployed, interactive prediction application.

Included

BI Dashboard Build

Design an interactive Power BI or Tableau dashboard for a real business use case.

Included

Machine Learning Model Lab

Train, tune and evaluate classification and regression models on real datasets.

What You'll Learn

What You'll Be Able to Do After This Data Science Certification

  • Apply statistics and probability to real data problems
  • Write efficient Python code for data analysis
  • Query and clean data using SQL and Pandas
  • Perform structured exploratory data analysis
  • Create clear, effective data visualizations
  • Build interactive dashboards in Power BI and Tableau
  • Build and evaluate machine learning models
  • Apply feature engineering and model tuning techniques
  • Deploy machine learning models as working applications
  • Use Docker and cloud basics for deployment
  • Communicate data-driven insights to stakeholders
  • Manage an end-to-end data science project lifecycle
Data Science Career Paths

Data Science Jobs: Data Analyst, Data Scientist & More

Data Analysis & BI

  • Data Analyst
  • Business Intelligence Analyst
  • Reporting Analyst

Data Science & ML

  • Junior Data Scientist
  • ML Engineer (Entry-Level)
  • Data Science Associate

Data Engineering

  • Junior Data Engineer
  • Data Wrangling Specialist
  • ETL Analyst

Analytics & Insights

  • Analytics Consultant
  • Insights Analyst
  • Product Analyst

Deployment & MLOps

  • ML / MLOps Engineer (Entry)
  • Applied Data Scientist

Advanced Career Paths

  • Senior Data Scientist
  • Data Science Team Lead
  • Chief Data Officer (long-term)
Role courses

Train for a specific Data Science role

The same programme, duration and fees, with the learning path arranged around one job role. Pick the role you want and see exactly what you will learn.

Data ScientistStatistical testing · Python and Pandas · SQL joinsView role course →ML EngineerClean Python code · Scikit-learn models · Model validationView role course →Data AnalystSQL queries · Pandas cleaning · Hypothesis testingView role course →BI AnalystPower BI dashboards · Tableau views · DAX basicsView role course →Data EngineerSQL joins · Data cleaning · Pandas reshapingView role course →Analytics ConsultantHypothesis-driven analysis · Statistical inference · Exploratory analysisView role course →
Salary Positioning

Data Science Salary in India & Globally — What to Expect

Figures are broad, indicative ranges for entry-to-mid-level roles and vary significantly by company, location, specialization and experience. They are not a guarantee of outcome.

India
₹4L – ₹10L / year

Typical entry-to-mid range for Data Analyst, Junior Data Scientist and BI Analyst roles, rising with certifications and project experience.

Global
$55K – $100K / year

Typical entry-to-mid range for equivalent data analyst and data scientist roles in mature international markets.

Certification Readiness

Certifications This Data Science Course Prepares You For

The curriculum is structured to help prepare learners for the following external certifications, including Google Data Analytics and IBM Data Science.

Google Data Analytics Professional Certificate
IBM Data Science Professional Certificate
Microsoft Certified: Power BI Data Analyst Associate
Tableau Desktop Specialist
AWS Certified Data Analytics – Specialty
Microsoft Certified: Azure Data Scientist Associate
Registration, fees and eligibility for any external certification exam are managed directly by the respective certifying body and may change over time. Skill IT Education awards its own course-completion certificate upon successful completion of the program.

Start your data science career with a structured, hands-on program

6 months total — 4 months of structured learning across eight modules, plus 2 months of real-time industry internship.

Start with Module 1Full Roadmap

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