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Data Science Course in Indore

Learn data science from highly-qualified mentors and earn a professional certification from one of the most trusted institutes in India. WsCube Tech offers the best data science course in Indore, introducing you to the dynamic field of data analysis. While pursuing the course, you work on several hands-on projects, acquire practical skills, get round-the-clock support, and interact with industry practitioners.

Our experts have curated extensive courses that cover technologies such as Python, R, Tableau, Machine Learning, Spark, and more. Join the leading data science training institute in Indore now and improve your technical and non-technical skills.

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Data Science offers ample professional opportunities worldwide. The subject focuses on extracting information from the massive dataset for actionable insights. It can be any data stored over the internet, from a person’s preferences and contact details to social media activities and whatnot.

Companies collect this raw data and add it to their data lake. However, they need a professional data scientist to structure and process unstructured data. Hence, it is no surprise that the demand for proficient data scientists has witnessed a great surge in the job market. However, there is a limited supply of skilled data scientists and our data science courses in Indore bridge that gap.

WsCube Tech is known for offering the most comprehensive and best data science course in Indore to learners from different walks of life. Our experienced mentors have curated an extensive curriculum that covers every topic from scratch.

Whether you are a freelancer, beginner, or working professional, our syllabus aligns with different learning goals. From data analysis and artificial intelligence to machine learning and more, our mentors cover every topic in detail during virtual and in-class training. You will also acquire essential data science skills, such as data collection, integration, extraction, statistical analysis, data mining, predictive analysis, and more.

Upon completing our data science training in Indore, you will receive a professional certificate from WsCube Tech, which is trusted by various leading companies. You will also get job assistance and the necessary professional guidance to kickstart a thriving career.

Data Science offers ample professional opportunities worldwide. The subject focuses on extracting information from the massive dataset for actionable insights. It can be any data stored over the internet, from a person’s preferences and contact details to social media activities and whatnot.

Companies collect this raw data and add it to

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Career Launch Countdown

Prepare to launch your career into the stratosphere with our intensive 7-day last-mile prep.

  • This comprehensive program offers placement assistance and interviews with top hiring managers.
  • Boost your employment prospects and exclusive referrals aimed at career readiness.
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Guided by the Geeks

Thrive under the mentorship of seasoned industry mentors who impart their vast knowledge and insights. Each session is crafted to help you navigate the complexities, boosting your confidence as you master the craft. Incorporate advanced techniques and strategies from industry gurus keen to share their hidden formulas for excellence.

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Project & Scenario-Based Curriculum

Step into engaging, hands-on sessions where learning meets real-world application. This program is crafted to enhance problem-solving skills by immersing you in projects that reflect real-world security challenges. 

  • Integrate theoretical knowledge with practical execution, refining your skills through active participation and collaboration.
  • Simulate real-world complexities by engaging through practical, hands-on mitigation.
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Cohort-Based Learning

Immerse yourself in a collaborative, cohort-based learning environment, prioritizing hands-on problem-solving abilities. Enhance your skills within a community that flourishes through shared growth.

  • Participate in projects and discussions that tackle real-world challenges, boosting your problem-solving skills with collaborative insights.
  • Take advantage of a strong support network where peers inspire each other, fostering a spirit of growth and shared achievements.
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LearnOffline Classes

Upskill yourself by gaining insights from leading professionals' vast experience.

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Practice

Sharpen your skills by learning through course assignments, live projects, and regular assessments and quizzes.

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Ask

Resolve your queries from industry experts with our dedicated 1:1 doubt-clearing sessions.

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Build

Craft a diverse portfolio and appealing resume, and optimize LinkedIn to showcase your data analytics skills.

Milestone 1 - Duration: 4 weeks

Build strong programming and database fundamentals through Python, pandas, and SQL. Learn how to clean, query, transform, and prepare real datasets like a true data professional.

Week 1

Python Essentials & Data Structures

  • Installing Python and setting up Jupyter
  • Understanding variables and data types
  • Using operators and expressions
  • Writing control flow (if/else, loops)
  • Handling errors and exceptions
  • Using lists, tuples and dictionaries
Week 2

Advanced Python & pandas Basics

  • Creating and reusing functions
  • Writing efficient list comprehensions
  • Understanding pandas Series and DataFrames
  • Loading data from CSV/Excel files
  • Filtering, sorting and selecting data
Week 3

SQL Fundamentals

  • Understanding relational databases
  • Writing basic SELECT queries
  • Filtering data with WHERE
  • Sorting and limiting results
  • Aggregating data with GROUP BY and HAVING
  • Joining multiple tables
Week 4

SQL Advanced

  • Writing subqueries
  • Using Common Table Expressions (CTEs)
  • Applying window functions (ROW_NUMBER, RANK, etc.)
  • Basics of query optimization

Case Study

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Nike Customer Purchase Analyzer

Build a Python tool that reads customer purchase data from a CSV/Excel file and provides quick insights using pandas.

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Swiggy Orders Analysis

Swiggy seeks insights from its SQL dataset. Implement sophisticated SQL queries with intricate joins for in-depth analysis and strategic decision-making.

Project:

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Apollo Hospitals Patient Flow SQL Lab

Milestone 2 - Duration: 2 weeks

Online data science course helping you master the art of cleaning messy data, exploring patterns, and extracting insights. Use Python visualizations & BI dashboards to tell compelling data stories.

Week 1

Data Cleaning & Preprocessing

  • Handling missing values
  • Identifying and removing duplicates
  • Detecting and treating outliers
  • Converting data types correctly
  • Working with dates and times
  • Creating derived features
Week 2

Python Visualization & EDA

  • Performing univariate analysis
  • Exploring relationships between variables
  • Creating histograms and boxplots
  • Building bar and line charts
  • Using pair plots for multivariate views
  • Applying visualization best practices

Case Study

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Zomato Order Quality Insights

As a data analyst at Zomato, work with raw order and delivery data to improve data quality and build reliable features for downstream analytics.

Project:

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JioHotstar Exploratory Data Analysis (EDA)

Milestone 3 - Duration: 5 weeks

Learn the core statistical thinking behind real-world ML problems. Build, evaluate, and refine regression and classification models used across industries.

Week 1

Descriptive Statistics & Distributions

  • Calculating mean, median and mode
  • Measuring spread with variance and standard deviation
  • Understanding quantiles and percentiles
  • Recognizing the normal distribution
  • Interpreting correlation between variables
Week 2

Probability & Hypothesis Testing

  • Learning basic probability rules
  • Understanding sampling and sample size
  • Building confidence intervals
  • Running t‑tests and chi‑square tests
  • Interpreting p‑values
  • Framing and analyzing A/B tests
Week 3

ML Foundations & Regression

  • Understanding supervised learning concepts
  • Splitting data into train and test sets
  • Applying cross‑validation
  • Building linear regression models
  • Scaling features where required
  • Evaluating models with regression metrics
Week 4

Regularization & Regression Refinement

  • Understanding overfitting and underfitting
  • Applying Ridge regression
  • Applying Lasso and elastic net
  • Handling multicollinearity
  • Using learning curves for diagnostics
Week 5

Classification Basics

  • Introducing classification problems
  • Building logistic regression models
  • Using k‑Nearest Neighbors (k‑NN)
  • Training decision trees
  • Evaluating with accuracy, precision and recall
  • Using F1‑score and ROC‑AUC
  • Understanding Time Series Analysis (Basics)

Case Study

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Amazon Homepage Experiment:

As a data scientist at Amazon, evaluate an A/B test on a new homepage layout aimed at increasing conversion rate.

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Swiggy Order Churn Classifier

As a data scientist at Swiggy, build a model to classify whether a customer is likely to stop ordering on the platform.

Project:

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Spotify Listener Stats Summary

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Uber Fare Prediction Model

Milestone 4 - Duration: 5 weeks

Level up with ensemble methods, clustering, PCA, and text-intelligence foundations. Choose between NLP or Deep Learning to build more advanced AI-driven systems.

Week 1

Tree Ensembles & Feature Engineering

  • Understanding ensemble learning
  • Training random forest models
  • Using gradient boosting methods
  • Interpreting feature importance
  • Encoding categorical variables
  • Building pipelines for preprocessing + modeling
Week 2

Unsupervised Learning

  • Introducing clustering problems
  • Applying k‑means clustering
  • Choosing k and reading silhouette scores
  • Understanding high‑dimensional data
  • Reducing dimensions with PCA
  • Interpreting explained variance
Week 3

Deep Learning or NLP Track

  • Understanding neural network building blocks
  • Learning activation and loss functions
  • Grasping gradient descent and backpropagation
  • Cleaning and tokenizing text (NLP track)
  • Representing text with TF‑IDF
  • Building simple text classification models
Week 4

Hyperparameter Tuning & Experimentation

  • Understanding hyperparameters vs parameters
  • Running grid search for tuning
  • Using random search for efficiency
  • Reading validation curves
  • Applying early stopping to prevent overfitting
  • Tracking experiments and results
Week 5

Model Evaluation & Interpretability

  • Performing detailed error analysis
  • Checking model calibration
  • Interpreting feature importance outputs
  • Using partial dependence ideas
  • Introducing fairness and bias concepts

Case Study

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Myntra Product Return Risk Model

As a data scientist at Myntra, build an ensemble model to predict the likelihood of a product being returned after purchase.

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MakeMyTrip Review Classifier

As an applied ML engineer at MakeMyTrip, build a neural‑network‑based system to classify hotel reviews as positive or negative.

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ICICI Bank Loan Fairness Audit

As a data scientist at ICICI Bank, review an existing loan‑approval model to ensure it is both accurate and fair.

Project:

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Netflix Content Recommender & View Forecasting

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Mercado Livre E‑commerce Delivery Tuning Lab

Milestone 5

A capstone project where learners solve a real business problem using data, analytics, and selective AI assistance. You will work on an end-to-end data science use case, from understanding the problem to analyzing data, building models, and generating insights that support business decisions. AI tools may be used to assist analysis, improve efficiency, and enhance insights, similar to how data teams work in modern organizations.

Business Problem & Data Understanding

  • Identify a real-world business problem and understand the data available to solve it.
  • Use data exploration and AI-assisted questioning to define objectives, success metrics, and scope.

Data Extraction & Preparation

  • Work with structured datasets using SQL and Python.
  • Clean, transform, and prepare data for analysis and modeling.

Exploratory Analysis & Insights

  • Perform exploratory data analysis to uncover trends, anomalies, and relationships.
  • Use visualizations, statistics, and AI-assisted summaries to highlight key insights.

Model Building & Evaluation

  • Apply machine learning techniques to address the business problem.
  • Train, evaluate, and compare models using appropriate metrics, with AI support for experimentation and tuning.

Insights, Decisions & Recommendations

  • Translate analysis and model outputs into clear business insights.
  • Use AI tools to help structure recommendations and explain results in business language.

Final Presentation

  • Present the complete solution, approach, and outcomes.
  • Demonstrate both analytical thinking and responsible use of AI in decision-making.
Milestone 6 - Duration: 4 weeks

Our Online Data Science Course includes a 4-week immersive internship where you work as a intern at WsCube Tech on real business challenges. Gain hands-on experience in data science, visualization, and reporting across multiple departments. Experience the real workflows of modern data teams while contributing to decision-driving projects.

Week 1

Data Collection & Python Foundations

  • Work with real business data using Python from day one
  • Clean, organize, and preprocess raw datasets using Pandas & NumPy
  • Write efficient SQL queries to extract and filter business data
  • Understand how data pipelines flow within an organization
Week 2

Statistical Analysis & Reporting

  • Apply statistical concepts to real company datasets
  • Identify trends, distributions, patterns, and anomalies
  • Perform hypothesis testing and correlation analysis on business data
  • Prepare structured analytical reports for team leads and stakeholders
Week 3

Supervised & Unsupervised ML Modelling

  • Build predictive models (regression, classification) on real business problems
  • Apply clustering and dimensionality reduction for customer/market segmentation
  • Evaluate and tune models for accuracy, precision, and business relevance
  • Translate model outputs into clear, actionable insights for non-technical audiences
Week 4

Insights & Stakeholder Presentation

  • Consolidate work from all previous weeks into a cohesive data science project
  • Craft a data-driven business narrative backed by statistical and ML findings
  • Present solutions and recommendations to WsCube Tech stakeholders
  • Demonstrate analytical thinking, Python/SQL proficiency, and communication skills
Bonus

BI Dashboards & Storytelling

  • Understanding measures vs dimensions
  • Defining business KPIs
  • Designing data models for BI tools
  • Adding slicers and interactive filters
  • Building executive‑ready dashboards

Data Pipelines & ETL

  • Understanding ETL vs ELT workflows
  • Ingesting data from files, APIs and databases
  • Designing end‑to‑end data workflows
  • Adding validation checks in pipelines
  • Implementing logging and basic monitoring

Databases, Warehousing & Big Data

  • Understanding database design
  • Schemas – Star & Snowflake
  • Understanding OLTP vs OLAP
  • Introducing data warehousing concepts
  • Getting an overview of Hadoop and Spark

Model Serving & APIs

  • Learning REST API fundamentals
  • Serializing and saving ML models
  • Designing batch inference workflows
  • Designing real‑time inference workflows
  • Considering basic security for ML APIs

Data Apps & Model Monitoring

  • Building interactive apps around models
  • Designing prediction input forms and outputs
  • Combining visualizations with model results
  • Tracking model performance over time

Advanced Topics & Electives

  • Understanding time series forecasting - advanced
  • Learning recommendation system approaches
  • Exploring advanced NLP tasks
  • Introducing modern language models

Data Ethics, Governance & Privacy

  • Recognizing different types of model bias
  • Evaluating fairness in ML decisions
  • Improving interpretability of models
  • Understanding data privacy regulations (GDPR/CCPA)
  • Learning core data governance principles

Generative AI & Large Language Models

  • Understanding how large language models work
  • Learning effective prompt engineering techniques
  • Knowing when and how to fine‑tune models
  • Introducing RAG (Retrieval‑Augmented Generation)
  • Applying ethical and responsible GenAI practices
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Resume Revamp

Upgrade and polish resumes to make them stand out to potential employers.

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LinkedIn Optimization

Optimize LinkedIn profiles to improve visibility and networking opportunities.

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GitHub Mastery

Enhance GitHub profiles to showcase your projects and collaboration skills.

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Portfolio Building

Develop & refine a professional portfolio to demonstrate skills & projects.

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Pitch Perfect

Improve verbal
communication and
presentation skills.

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Job Ready

Climb the ladder that leads you to your dream job.

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Resume Revamp

Upgrade and polish resumes to make them stand out to potential employers.

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LinkedIn Optimization

Optimize LinkedIn profiles to improve visibility and networking opportunities.

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Industry-Recognized Certificate

Earn a certificate valued by top companies.

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Stand Out in Job Market

Fortify your profile to increase credibility.

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Your Passport to Career Growth

Access well-paying positions in your field.

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Industry-Recognized Certificate

Earn a certificate valued by top companies.

Our learners work at top companies

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    Total Program Fee:

    27,700/-

    17,699/-

    • Live instruction from Industry Veterans
    • Official certification in Human Resources
    • Vibrant community just like a College Campus
    • Hand-on curriculum with Real-Life Projects
Mentore

Kushagra Bhatia

Founder

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Mentore

Ayushi Jain

Lead Data Analyst

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Mentore

Bhawani Singh

Data Analyst Trainer

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Secure your spot quickly, seats are filling fast! Don’t miss out—enroll now and take the first step towards transforming your career!

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Placement Report 2025-26

Get the complete report to explore all program outcomes.

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Students Placed

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Highest Package

Data Science is applied across most industries and is considered one of the most sought-after skills in the IT sector. It combines statistics, data analysis, scientific methods, artificial intelligence, and machine learning. The purpose of the field is to seek value from heaps of data collected from different sources.

A professional data scientist collects a large amount of data, gets insights, and analyzes it. They apply their analytical and technical skills to provide solutions to several business challenges.

They are responsible for finding valuable insights by analyzing massive datasets. So, their core tasks are to cleanse, aggregate, manipulate, and study data to help make data-driven decisions.

As an accomplished and skilled data scientist, you can apply for the following job roles:

  • Data Architect and Administrator
  • Data Mining Engineer
  • Data Analyst
  • Data Scientist
  • Team Lead- Data Engineer
  • Machine Learning Engineer
  • Business Analyst
  • Marketing Analyst
  • Statistician and Mathematician
You don’t need any specific academic degree or professional experience to sign up for our data science training in Indore. Freelancers, business owners, graduates, freshers, and working professionals from any field are welcome to join our community.

Our data science course covers all areas and aspects of the field, including:

  • Part-I: Python
  • PART-II: Data Analysis With Statistics And Visualization
  • Part-III: Machine Learning
  • Part-IV: Deep Learning, AI, Neural Network
Data science is surely a promising career option and will offer ample opportunities in the coming years. This versatile field allows you to work across multiple industries, such as finance, education, healthcare, information technology, and more. Moreover, it offers several secure and high-paying job vacancies, which you can select based on your interest and expertise.
The average salary of a beginner-level data scientist is ₹8 LPA, and with years of experience and expertise in the field, you can make around ₹35 LPA and more.
Our data science course spans 6 months.
Coding or programming is not a necessary skill to enrol in our data science courses in Indore. Having basic technical knowledge may be beneficial, but it doesn’t define your efficiency or learning capabilities.
The fee for our data scientist course in Indore is 5 months, which includes hands-on projects and job assistance.