Data Science

The Data Science course equips you with the skills to analyze and interpret complex data. Learn Python, statistics, machine learning, and data visualization to make data-driven decisions. This course is designed for beginners and professionals looking to enhance their analytical skills and build a career in data science.

Placement Assistance Program*

Course Details

Instructor:

Industry Expert with 5+ years of experience

Difficulty Level:

Beginner to Intermediate

Duration:

8 to 9 month

Mode:

Online and offline

Course Content

Preparatory Sessions –Python

Get started with Python through our structured preparatory sessions. Learn the fundamentals, explore essential tools, and gain hands-on experience with guided practice to build a strong programming foundation.

Master the art of data manipulation with SQL. From foundational concepts to advanced techniques, explore SQL basics, optimize performance, and dive deep into user-defined functions for efficient data processing.

Harness the power of Python’s top libraries for data science. Learn to handle data with NumPy, manipulate datasets using Pandas, preprocess data effectively, and create insightful visualizations.

Build a strong foundation in inferential statistics and prescriptive analytics. Learn to leverage Python for descriptive, diagnostic, and predictive statistical analysis to derive meaningful insights from data.

Explore the core concepts of machine learning, from regression and classification to clustering techniques. Gain hands-on experience in building predictive models using real-world datasets.

Master supervised learning techniques, including regression models, decision trees, random forests, and support vector machines. Learn to evaluate model performance using classification reports, confusion matrices, and time series forecasting.

Understand unsupervised learning methods like K-means clustering and dimensionality reduction techniques such as PCA and LDA. Learn how to uncover hidden patterns in data without labeled outputs

Dive deeper into machine learning with advanced techniques like bagging, boosting, and predictive analytics. Explore cognitive science applications to enhance model performance.

Learn to handle big data efficiently using Apache Spark. Understand RDDs, advanced Spark concepts, and the integration of Spark with Hive for large-scale data processing.

Discover the fundamentals of artificial intelligence and deep learning. Explore neural networks and TensorFlow to build and train deep learning models.

Unlock the power of NLP with text mining, sentiment analysis, and sequence modeling. Learn to build AI-driven chatbots and recommendation engines.

Gain expertise in data visualization and analytics using Power BI. Learn DAX, create interactive dashboards, and perform hands-on exercises to turn raw data into actionable insights.

Understand MLOps principles for deploying and managing machine learning models in production. Learn best practices for automation, monitoring, and scalability.

Apply your knowledge to a real-world data science project. Work on an end-to-end problem statement, integrating machine learning, deep learning, and data visualization techniques.

Fee Structure

Total Fee: ₹ 1,99,999/-
Introductory Offer: ₹ 1,49,999/- (+GST)

With our affordable EMI option, your fee can be as low as ₹ 8,333/- month

What’s Included

Tools to Master

Requirements

  • Basic understanding of mathematics and statistics
  • No prior programming experience required
  • Suitable for students, working professionals, and career switchers

3-4 Years after Program

Our Alumni work at top companies

FeeAmount (excl. tax)Due Date
Registration FeeINR 25,000To be paid upon the acceptance of the offer letter
Remaining fee payableINR 95,000To be paid as per the fee structure given by institution
TotalINR 1,20,000 (+GST)
Weekend only classes

Classes are scheduled exclusively on weekend, with sessions talking place on Saturday & Sunday 

3 Guaranteed Interviews

* Subject to the terms & conditions stated in the career service policy

** Based on experience & performance

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