In-Demand IT Career 2026

Data Science Course in Indore

Name: Placement Adda
Address: 5, Vishnu Puri, 103, Sukhmani Apartment, Above Union Bank AB Road, Bhawarkua Main Rd, Indore, Madhya Pradesh, 452014, IN
Telephone: +91-9644704844
Price range: ₹₹

DATAData Science is the multidisciplinary field that combines statistical mathematics, programming algorithms, and domain expertise to extract meaningful insights and predictive intelligence from raw business data. In today's digital era, data-driven decisions power every forward-looking corporation, from e-commerce recommendations and financial fraud detection to healthcare diagnostics.

At Placement Adda in Bhawarkua, Indore, our Data Science with Python and Machine Learning program provides intensive, practical training designed for college freshers, engineers, and working professionals. You will master foundational Python, advanced data wrangling with NumPy and Pandas, applied statistics, SQL querying, exploratory data analysis, and predictive machine learning models through real-world Kaggle datasets.

Why Learn Data Science at Placement Adda?

80% Hands-on Coding − Write real code from day one in Jupyter Notebooks and Google Colab rather than passive theory slides.

End-to-End Analytics Pipeline − Master every phase of the data lifecycle: Data Ingestion, Data Cleaning, EDA, Feature Engineering, Model Training, and Evaluation.

Real-world Datasets − Train predictive models on real-life datasets from banking, healthcare, retail, and telecommunications.

Dedicated Indore Lab Mentorship − Get hands-on doubt resolution and project guidance from experienced industry practitioners at our Bhawarkua training center.

Who Should Enroll in This Course?

Engineering & Science Graduates (B.Tech, BE, BCA, MCA, B.Sc) − Build in-demand algorithmic problem-solving and machine learning skills to secure high-growth data roles.

Maths & Statistics Enthusiasts − Apply theoretical mathematical foundations to practical machine learning and statistical modeling problems.

Working Professionals & Data Analysts − Transition from reporting, manual Excel, or legacy IT into high-paying Data Scientist and Machine Learning Engineer careers.

BATCH ADMISSIONS OPEN

Data Science Accelerator

Bhawarkua, Indore | Offline Classroom & Interactive Live Online

Course Duration 4 to 6 Months

Batch Timings Regular & Weekend Batches

Practical Exposure 80% Coding & Labs

Capstone Projects 5+ Real-world Projects

Prerequisites Basic Math / No Prior Coding

Placement Assistance Mock Interviews & Resume Prep

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Data Science Course Curriculum & Modules

Python & Data Wrangling

Statistics, EDA & SQL

Machine Learning

Data Science Lab Projects & Placement

Python Programming Fundamentals

Python 3 Architecture, Variables, Keywords & Data Types
Control Flow Statements (If-Else, While & For Loops)
Data Structures: Lists, Tuples, Dictionaries, Sets & Comprehensions
Functions, Lambda Expressions, *args & **kwargs
Object-Oriented Programming (OOP): Classes, Objects, Inheritance
File I/O (CSV, JSON, Text) & Exception Handling in Python

NumPy, Pandas & Data Wrangling

NumPy: N-Dimensional Arrays, Indexing, Slicing & Broadcasting
Mathematical & Statistical Operations with NumPy
Pandas: Series, DataFrames & Reading Heterogeneous Data Sources
Data Cleaning: Handling Missing Values (Imputation), Deduplication
Data Transformation: GroupBy, Pivot Tables, Merging & Concatenation
String Manipulation & Date/Time Series Operations

Applied Statistics & Probability

Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation
Probability Distributions (Normal, Binomial, Poisson Distributions)
Central Limit Theorem, Confidence Intervals & Standard Error
Inferential Statistics & Hypothesis Testing (Z-test, T-test, ANOVA)
P-Value Interpretation, Type I and Type II Errors
Correlation Analysis: Pearson & Spearman Rank Correlation

SQL & Data Visualization (EDA)

SQL for Data Science: SELECT, WHERE, ORDER BY, GROUP BY & HAVING
Multi-Table Relations: INNER, LEFT, RIGHT, FULL OUTER JOINS & Unions
Subqueries, Common Table Expressions (CTEs) & Window Functions
Connecting Python to Relational Databases (SQLite, MySQL, SQLAlchemy)
Data Visualization with Matplotlib (Line charts, Histograms, Scatter plots)
Advanced Statistical Plots with Seaborn (Heatmaps, Pairplots, Boxplots)

Supervised Machine Learning

Introduction to ML: Problem Formulation & Train-Test Splits
Linear Regression: Cost Function, Gradient Descent, OLS & Multi-collinearity
Logistic Regression: Sigmoid Function, Odds Ratio & Binary Classification
Decision Trees & Random Forest Classifiers (Ensemble Learning)
Support Vector Machines (SVM) & K-Nearest Neighbors (KNN)
Model Evaluation: Confusion Matrix, Precision, Recall, F1 & ROC-AUC

Unsupervised Learning & Model Tuning

K-Means Clustering & Finding Optimal K using the Elbow Method
Hierarchical Clustering & Dendrogram Analysis
Dimensionality Reduction: Principal Component Analysis (PCA)
Feature Scaling (StandardScaler, MinMaxScaler) & One-Hot Encoding
Hyperparameter Tuning with GridSearchCV and RandomizedSearchCV
Overfitting vs Underfitting: Regularization (L1 Lasso, L2 Ridge)

Lab12x7 Dedicated Practice Lab Facility − Students get continuous access to high-speed coding machines equipped with Anaconda, Jupyter, Python, and SQL servers at our Bhawarkua center.

500+500+ Real Coding Challenges − Solve progressive problems covering Python data manipulation, SQL joins, probability puzzles, and model optimization.

1-on-1Personal Doubt Resolution − Dedicated mentors and data scientists assist you live in the lab for debugging code, optimizing algorithms, and tuning models.

Real-World Capstone Projects

Graduate with an impressive GitHub portfolio demonstrating end-to-end data analysis and predictive modeling capabilities:

Customer Churn Prediction: Build classification models to identify at-risk telecom customers using Scikit-learn and feature importance.
Real Estate Valuation Engine: Predict residential property prices using multivariate regression and regularized Ridge/Lasso models.
Retail Customer Segmentation: Implement unsupervised K-Means clustering to identify high-value customer purchasing personas.
Credit Card Fraud Detection: Handle highly imbalanced transactional datasets using SMOTE and ROC-AUC evaluation.

Placement Assistance & Interview Prep

Placement Adda provides dedicated career services to prepare students for technical interviews and recruitment drives:

ATS Resume Engineering: Craft industry-standard CVs highlighting practical project outcomes, GitHub links, and technical skill tags.
300+ Technical Questions: Thorough preparation covering Python coding, SQL queries, probability scenarios, and ML algorithms.
Mock Interview Drills: 1-on-1 technical and HR mock rounds with working data scientists to build interview confidence.
Target Roles: Data Scientist Trainee, Junior ML Engineer, Data Analyst, Business Intelligence Analyst.

HAVE QUESTIONS?

Frequently Asked Questions

Find clear answers regarding our Data Science training program in Indore.

Which institute offers the best Data Science course in Indore?

Placement Adda is recognized as one of the leading IT training institutes in Indore, located at Bhawarkua. We deliver hands-on training with Python, Statistics, SQL, and Machine Learning using real datasets, combined with dedicated lab mentorship and placement preparation.

What is the duration and fee structure of the Data Science course?

The Data Science course spans 4 to 6 months with flexible weekday and weekend batches. Fees are affordable and structured with installment options. Contact our admissions team directly via WhatsApp or phone to enquire about current batch fees and early-bird scholarship discounts.

Can freshers or non-programmers learn Data Science?

Yes. Our curriculum begins from absolute zero in Python programming and high school-level mathematical foundations. As long as you have logical reasoning and dedication, our step-by-step guidance will make you confident in coding and machine learning.

What is the difference between Data Science and Data Analytics?

Data Analytics focuses on analyzing historical data using BI tools like Tableau, Power BI, and SQL to answer "what happened?". Data Science utilizes advanced Python algorithms, statistical modeling, and Machine Learning to forecast "what will happen?" and automate intelligent decisions.

Do you provide placement support for Data Science students?

Yes. Placement Adda provides comprehensive career assistance including GitHub technical portfolio creation, ATS resume formatting, 300+ interview questions, and 1-on-1 mock interviews to prepare you for hiring rounds.

Are offline classroom batches available in Indore?

Yes, offline classroom training is conducted at our main institute in Bhawarkua, Indore. Students have full access to our physical coding labs and faculty mentors. Interactive online sessions are also supported for remote learners.

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DATA SCIENCE