Data & AI

Data Science

Turn Data into Insights with Data Science

Learn how to collect, clean, analyze, visualize, and interpret data using Python, statistics, data analysis techniques, and machine learning fundamentals.

Build practical data-science skills through hands-on datasets, exploratory analysis, visualization, and real-world data projects.

Data Science

ConsivoX Certified

16 Modules • Live Mentorship

Course Highlights

Duration

16 – 32 Hours

Learning Tracks

Foundation • Professional • Advanced

Level

Beginner to Advanced

Curriculum Scope

16 Modules • Live Mentorship

Practical Focus

Hands-On Case Studies & Labs

Hands-On

Live & Capstone Development

Outcome

Real-World Production Projects

Credential

Certificate of Completion

Core Outcomes

What You'll Learn

Key Competencies
Data Science fundamentals
Python for Data Science
NumPy fundamentals
Pandas for data manipulation
Data cleaning and preprocessing
Exploratory Data Analysis

Why Learn Data Science?

Data Science combines programming, statistics, data analysis, visualization, and machine learning to extract useful insights from data and support better decision-making.

Industry-Aligned Curriculum

Gain practical mastery of Data Science concepts matching modern production standards.

Hands-On Project Building

Develop production-grade applications and case studies directly for your professional portfolio.

Career & Interview Readiness

Acquire the technical confidence and problem-solving skills required for high-impact roles.

FLEXIBLE FORMATS

Data Science — Modes of Learning

Choose the learning mode that fits your schedule, lifestyle, and career goals with hands-on practice built in.

16 Hours

Foundation

₹5,500 • 16 Hours

Master essential foundations with live instructor-led sessions, 6-month LMS access, and core learning materials.

16+ Hours of Live Instructor-Led Sessions
LMS Access for 6 Months
Course Materials & Learning Resources
Most Popular

Professional

₹7,500 • 24 Hours

Elevate your practical skills with 1:1 doubt clearing sessions, dedicated mentor support, and extended lab work.

24+ Hours of Live Instructor-Led Sessions
One-on-One Doubt Clearing Sessions
LMS Access for 6 Months
Dedicated Mentor Support
Career Track

Advanced

₹9,000 • 32 Hours

Comprehensive career masterclass featuring extensive live sessions, 1:1 mentor syncs, interview prep, and placement guidance.

32+ Hours of Live Instructor-Led Sessions
One-on-One Doubt Clearing Sessions
LMS Access for 6 Months
Dedicated Mentor Support
Placement Guidance
Interview Assistance
STRUCTURED ROADMAP

Data Science Curriculum

Step-by-step learning progression designed for practical mastery, from fundamentals to production-ready deployment.

16 Modules16+ Hours Live & Hands-On

Key Concepts Covered:

  • What is Data Science?
  • Data Science Lifecycle
  • Types of Data
  • Data Science Applications
  • Data Science Workflow

Key Concepts Covered:

  • Python Fundamentals
  • Variables and Data Types
  • Conditions and Loops
  • Functions
  • Lists, Tuples and Dictionaries

Key Concepts Covered:

  • Introduction to NumPy
  • NumPy Arrays
  • Array Indexing and Slicing
  • Array Operations
  • Basic Statistical Operations

Key Concepts Covered:

  • Introduction to Pandas
  • Series and DataFrames
  • Loading Data
  • Selecting and Filtering Data
  • Basic DataFrame Operations

Key Concepts Covered:

  • Understanding Data Quality
  • Handling Missing Values
  • Removing Duplicates
  • Data Type Conversion
  • Data Transformation

Key Concepts Covered:

  • What is EDA?
  • Understanding Dataset Structure
  • Descriptive Analysis
  • Identifying Patterns and Outliers
  • Generating Data Insights

Key Concepts Covered:

  • Mean, Median and Mode
  • Range and Variance
  • Standard Deviation
  • Percentiles and Quartiles
  • Statistical Interpretation

Key Concepts Covered:

  • Visualization Fundamentals
  • Bar and Line Charts
  • Histograms
  • Scatter Plots
  • Visualization Best Practices

Key Concepts Covered:

  • Understanding Correlation
  • Positive and Negative Correlation
  • Correlation Matrices
  • Identifying Relationships
  • Correlation vs Causation

Key Concepts Covered:

  • Understanding Features
  • Feature Selection
  • Creating New Features
  • Encoding Categorical Data
  • Feature Scaling

Key Concepts Covered:

  • What is Machine Learning?
  • Machine Learning Workflow
  • Supervised vs Unsupervised Learning
  • Training and Testing Data
  • Machine Learning Applications

Key Concepts Covered:

  • Regression Fundamentals
  • Linear Regression
  • Feature and Target Variables
  • Making Predictions
  • Regression Evaluation

Key Concepts Covered:

  • Classification Fundamentals
  • Classification Problems
  • Logistic Regression
  • Decision Tree Concepts
  • Classification Predictions

Key Concepts Covered:

  • Why Model Evaluation Matters
  • Accuracy and Error
  • Confusion Matrix
  • Precision and Recall
  • Training vs Testing Performance

Key Concepts Covered:

  • Problem Definition
  • Dataset Collection and Preparation
  • Data Cleaning and Exploration
  • Visualization and Analysis
  • Building and Evaluating a Model
  • Practical Project
  • Customer Churn Analysis & Prediction
  • Analyze customer data to identify patterns associated with customer churn and build a basic predictive model.
  • Project Workflow
  • Data → Cleaning → EDA → Visualization → Feature Preparation → Model → Evaluation → Insights

Key Concepts Covered:

  • End-to-End Data Science Workflow
  • Data Analysis Problem Solving
  • Model Interpretation
  • Project Presentation
  • Data Science Career Roadmap
  • Final Activity
  • Complete an end-to-end data-science case study involving data preparation, exploratory analysis, visualization, modeling, evaluation, and presentation of insights.

Everything You Need to Master Data Science

Comprehensive technical foundation, modern tooling, and production workflows packed into a focused, hands-on curriculum.

Python for Data Science

Master core Data Science principles, scalable architectures, and practical techniques.

NumPy & Pandas

Learn Python fundamentals and use them to work with datasets and perform data-analysis tasks.

Data Cleaning

Work with arrays, DataFrames, filtering, transformation, and structured data manipulation.

Exploratory Data Analysis

Learn how to identify and handle missing, duplicated, inconsistent, and incorrectly formatted data.

Data Visualization

Explore datasets systematically to identify trends, patterns, distributions, and anomalies.

Statistics Fundamentals

Create charts and visual representations that make complex datasets easier to understand.

Real-World Projects You'll Build

Build production-grade applications that demonstrate your skills to engineering recruiters and hiring managers.

Capstone SpotlightData & AI Project

Sales Data Analysis

Build

Key Features:

  • Analyze a sales dataset to identify business trends and performance patterns.
  • Data cleaning
  • Sales analysis
  • Product analysis
  • Regional analysis
  • Trend visualization
  • Business insights
Data ScienceConsivoXPortfolio
Production Ready
Project 02Data & AI Project

Student Performance Analysis

Build

Key Features:

  • Analyze student data to understand factors associated with academic performance.
  • Student data cleaning
  • Performance analysis
  • Subject-wise comparison
  • Correlation analysis
  • Visualization
  • Insight generation
Data ScienceConsivoXPortfolio
Production Ready
Project 03Data & AI Project

Customer Churn Analysis

Build

Key Features:

  • Analyze customer data to identify patterns associated with customer churn.
  • Customer data exploration
  • Churn analysis
  • Feature preparation
  • Visualization
  • Customer segmentation concepts
  • Insight generation
Data ScienceConsivoXPortfolio
Production Ready
Project 04Data & AI Project

House Price Prediction

Build

Key Features:

  • Create a basic machine-learning model to predict house prices based on available features.
  • Dataset preparation
  • Feature selection
  • Data preprocessing
  • Linear regression
  • Prediction
  • Model evaluation
  • FINAL PROJECT — Complete Data Science Challenge
  • Complete an end-to-end Data Science project using:
  • Data Collection → Data Cleaning → EDA → Visualization → Feature Engineering → Model Building → Evaluation → Insights → Presentation
  • The final project can serve as a practical demonstration of the learner's introductory Data Science skills.
Data ScienceConsivoXPortfolio
Production Ready
OFFICIAL CREDENTIALS

Government Recognized Industry Certification

Earn authentic, verifiable credentials recognized by industry leaders and verified via Startup India, MSME, and the Ministry of Corporate Affairs.

TIER 01 • Silver PerformerSilver Performer

Silver Certificate

Validates core engineering fluency, active internship engagement, and successful project submissions.

100% completion of course modules & domain internship tasks
Practical evaluation across live project milestones
Code submissions reviewed and approved by mentors
Unique QR code verification valid for lifetime authentication
Verified Internship Credential & LinkedIn Badge
Silver Certificate — ConsivoX Solutions
View Full Certificate
Official QR & Govt. AccreditedClick to Enlarge

Government & Corporate Recognition

Accredited under Startup India, MSME, and Ministry of Corporate Affairs.

Verifiable Dynamic QR Code

Instant online validation for recruiters and hiring managers.

LinkedIn One-Click Integration

Seamlessly showcase verified credentials on your professional profile.

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