Data Science Course in Pune

Practical Oriented Training

Master Data Science with our hands-on training! Learn advanced techniques and boost your career in this high-demand field. Enroll now!

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Course Information

Comprehensive details about course content, structure & objectives.

1-on-1
Training

Training that is specifically customized to meet each student's needs.​

Classroom Training

Live interactive sessions on the course with experienced instructors.

Online
Guidance

Flexible virtual support for effective remote and distant learning.

Key Notes

Expert Faculties

Key Features

Placement Support

Key Features

Resume Building

Key Features

Real-Time Project

Key Features

Guaranteed Certification

Key Features

Experience Alteration System

Key Features

Expert Faculties: Learn from seasoned professionals with  extensive industry experience and knowledge.

Placement Support: Comprehensive career guidance and job placement assistance to ensure students secure their desired job roles.

Resume Building: Craft impressive resumes to highlight your skills and achievements effectively.

Real-Time Project: Engage in practical projects to apply data science concepts in real-world.

Guaranteed Certification: Earn a recognized certification upon successful course completion.

Experience Alteration System: Experience real-world projects and hands-on training, ensuring you are job-ready.

What is Data Science?

Data Science is about using data to answer questions and solve problems. It involves gathering data, cleaning it up, and analyzing it to find useful patterns and trends. In a Data Science Course in Pune, you’ll learn how to use different tools and techniques to make sense of data, create visualizations, and build models that predict future outcomes. This helps businesses make smarter decisions, understand their performance better, and stay ahead of their competitors. In simple terms, Data Science turns raw data into valuable insights that can drive success.

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Who Can Apply For Data Science Course?

  1. Recent Graduates
  2. Working Professionals
  3. Career Switchers
  4. Researchers and Academics
  5. Entrepreneurs and Business Owners
  6. Students
  7. IT Professionals
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Data Scientist's Skills

Python

SQL

MLOps

Generative AI

ChatGPT

Inferential Statistics

Data Analysis

Data Science

Story Telling

Data Visualization

Artificial Intelligence

Large Learning Models

Supervised & Unsupervised 

Mathematical Modeling

Descriptive Statistics

Data Science Syllabus

The Data Science Course syllabus includes data analysis, statistical methods, machine learning, and data visualization. It also covers programming languages such as Python and R, big data technologies, data mining, and predictive modeling. The course provides practical exercises and real-world case studies to enhance learning.

Interview Q&A

Answer: Supervised learning involves training a model on labeled data, meaning the input data is paired with the correct output. Examples include classification and regression tasks. Unsupervised learning involves training a model on data without labeled responses and is used to find hidden patterns or intrinsic structures in the data, such as clustering and association tasks.

Answer: Overfitting occurs when a model learns the training data too well, including its noise and outliers, leading to poor performance on unseen data. It can be prevented by using techniques such as cross-validation, pruning (in decision trees), regularization methods (like Lasso or Ridge regression), and reducing the complexity of the model.

Answer: The steps typically include: defining the problem, collecting data, cleaning and preprocessing data, exploratory data analysis (EDA), feature engineering, selecting and training a model, evaluating the model, tuning hyperparameters, and finally deploying the model and monitoring its performance.