Data Science Course in Kolkata
Master predictive intelligence and machine learning with the Data Science Course in Kolkata at Acesoftech Academy. Master Python, SQL, statistical modeling, machine learning algorithms, deep learning, and cloud deployment with 100% placement support.
Accelerate Your Technical Career in Kolkata
Data science blends computer science, statistics, and machine learning to build intelligent systems. For business analytics and dashboarding focus, view our Data Analytics Course in Kolkata. To explore specialized deep neural architectures, check our Machine Learning Course in Kolkata and Artificial Intelligence Course in Kolkata.
Comprehensive 12-Module Curriculum
Mathematics & Statistics for Data Science
Linear algebra, matrix operations, multivariable calculus, probability, and hypothesis testing.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Python Data Science Stack
NumPy vectorization, Pandas DataFrames, and scientific computing with SciPy.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Exploratory Data Analysis & Visualization
Feature distributions, outlier detection with IQR/Z-score, and Seaborn visual aesthetics.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Advanced SQL for Data Scientists
Window functions, common table expressions, query optimization, and data extraction.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Supervised Learning: Regression Algorithms
Linear regression, polynomial regression, ridge/lasso regularization, and evaluation metrics.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Supervised Learning: Classification Models
Logistic regression, decision trees, random forests, SVM, and ROC-AUC curves.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Unsupervised Learning & Clustering
K-Means clustering, hierarchical clustering, DBSCAN, and PCA dimensionality reduction.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Ensemble Techniques & Gradient Boosting
Bagging, boosting, AdaBoost, Gradient Boosting, XGBoost, and LightGBM.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Natural Language Processing (NLP)
Tokenization, lemmatization, TF-IDF, word embeddings (Word2Vec), and sentiment analysis.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Deep Learning Foundations with PyTorch
Artificial neural networks, backpropagation, activation functions, and optimizer tuning.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Model Deployment & MLOps
Building REST APIs with FastAPI, containerizing with Docker, and cloud hosting on AWS.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
Capstone Data Science Project & Placement
End-to-end machine learning project with portfolio defense and mock interviews.
- Industry-aligned hands-on practical exercises
- Enterprise architectural patterns and best practices
- Production-grade deployment and real-time debugging
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Frequently Asked Questions
The Data Science course is a comprehensive 6-month hands-on program.
Basic high school mathematics is helpful; we teach all statistical and machine learning concepts from the ground up.
Yes, 100% placement support is guaranteed with mock technical rounds and corporate recruitment drives.
Python, SQL, NumPy, Pandas, Scikit-Learn, PyTorch, XGBoost, FastAPI, and Docker.
Yes, you will build and deploy multiple predictive machine learning models to production servers.
Weekday intensive batches and weekend flexible classes are available for working professionals.
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