Best Data Science Course in Indore with Job Placement

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Data Science
Duration 20 Weeks

Start your career with the best Data Science Course in Indore. Gain hands-on training in Python, SQL, and machine learning in a 20-week bootcamp.

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Leading Companies Hiring Our Learners

Explore Your Career Opportunities

Discover the in-demand job opportunities available after completing this course.

Data Scientist

₹8 – 12 LPA

Machine Learning Engineer

₹10 – 18 LPA

Business Intelligence Analyst

₹8 – 18 LPA

Product Analyst

₹9 – 15 LPA

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95%

Placement Rate

1000+

Students Trained

12L

Highest CTC

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What you’ll learn in 20 Weeks?

Our Data Science Course in Indore is designed to help you learn the most in-demand skills for today’s tech industry. Offered by a top data science institute in Indore, the course focuses

Programming & Data Handling: Master Python and SQL for data manipulation and analysis through hands-on training in our data science training in Indore.

Statistical Analysis & Machine Learning: Gain practical knowledge in statistical techniques and machine learning algorithms as part of a certified data science course in Indore

Real-World Projects: Work on practical projects that mirror current industry challenges and help build your portfolio with guidance from experts at the best data science training institute in Indore.

Module 1

Python Mastery for Data Science

  • Getting started: IDEs (Jupyter, PyCharm), setup & environments
  • Core Python: Variables, Data Types, Operators, Conditionals, Loops
  • Functional Python: Functions, Lambdas
  • Pythonic Thinking: List comprehensions, error handling, modules
  • Object-Oriented Python: Classes, Inheritance, Encapsulation
Module 2

Data Handling & Visualization with Python

  • NumPy: Arrays, indexing, vectorized operations, math & stats
  • Pandas: Series, DataFrames, cleaning, transformation, group operations
  • Data Merging, Filtering, and Reshaping Techniques
  • Data Visualization: Matplotlib essentials and Seaborn for advanced plots
Module 3

Exploratory Data Analysis & Statistics

  • Univariate, Bivariate, Multivariate Analysis
  • Mean, Median, Mode, Variance, Standard Deviation
  • Correlation, Covariance, and Distribution Patterns
  • Probability Concepts and Statistical Tests
  • Data Health Check: Missing values, outliers, data quality
Module 4

SQL for Data Insights

  • Introduction to Relational Databases and SQL Syntax
  • Data Retrieval with SELECT, WHERE, GROUP BY, ORDER BY
  • Combining Data with JOINs and Subqueries
  • Window Functions and Aggregations
Module 5

Data Visualization with Power BI

  • Power BI Overview & Installation
  • Power Query: Data Transformation
  • Data Modeling & Relationships
  • Writing DAX Functions
  • Creating Visuals and Reports
  • Dashboards & Sharing Online
Module 6

Data Visualization with Tableau

  • Tableau Interface & Navigation
  • Connecting to Various Data Sources
  • Worksheets, Dashboards, Stories
  • Filters, Parameters, Calculated Fields
  • Advanced Visuals & Interactivity
Module 7

Machine Learning Fundamentals & Feature Engineering

  • Machine Learning Workflow and Use Cases
  • Data Splitting: Train/Test, Cross-Validation
  • Feature Engineering: Encoding, Scaling, Transformation
  • Missing Data Imputation and Handling Imbalance
  • Introduction to scikit-learn and Pipelines
Module 8

Supervised & Unsupervised Learning in Action

  • Supervised: Linear/Logistic Regression, KNN, Decision Trees, Random Forest, Naive Bayes
  • Unsupervised: K-Means, Hierarchical Clustering, PCA
  • Evaluation Metrics: Confusion Matrix, F1 Score
Module 9

Foundations of Deep Learning

  • Neural Networks: Architecture, Neurons, Activation Functions
  • Forward & Backpropagation, Optimizers: SGD, Adam
  • Loss Functions, TensorFlow & Keras
  • Model Types: Dense Networks and Intro to CNNs
Module 10

Natural Language Processing with Python

  • Text Preprocessing: Tokenization, Stemming, Lemmatization
  • Feature Extraction: Bag-of-Words, TF-IDF, Word Embeddings
  • Building NLP Models: Text Classification, Sentiment Analysis
  • Intro to Transformers & BERT
Module 11

Generative AI and LLMs

  • Introduction to Generative AI
  • Overview of Large Language Models (LLMs)
  • Working with Pretrained Models
  • Prompt Engineering & LangChain Basics
  • Retrieval-Augmented Generation (RAG)
  • Ethical Considerations in Generative AI

Want the full 15+ module list?

Download the brochure to view the detailed curriculum and course flow.

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Frequently asked Questions

Check out some frequently asked questions.

You don’t need any prior experience to join. This course is beginner-friendly — just a basic understanding of computers and curiosity about data is enough to start.

You'll learn Python, SQL, statistics, data analysis, machine learning, and data visualization — all with hands-on practice on real-world projects to build your skills.

During the data science certification course in Indore, you’ll work with tools like Python, Pandas, NumPy, Scikit-learn, and Matplotlib — all essential for real-world data science work.

After completing the course, you’ll be ready for roles such as Data Analyst, Machine Learning Engineer, or Data Scientist in various industries.

Yes, you’ll get full career support including help with portfolio creation, resume updates, interview preparation, and job search guidance.

We continue supporting you even after course completion through expert sessions and a strong learner community network.

The course fee depends on its duration and format. We offer flexible payment options to make it easier for you to get started with your learning journey.

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