Full-Stack Data Science Mastery

Full-Stack Data Science Mastery

Master Python, Machine Learning, Deep Learning, and Generative AI. Build and deploy real-world AI systems.

βœ” ISO 9001:2015 Certified Training Program
Created by Principal Data Scientist
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β‚Ή5000 β‚Ή8000 50% OFF
2 days left at this price!
  • 48+ structured modules
  • Real-world projects
  • Certificate of completion
  • Lifetime access
  • Industry use cases

Data Science Tools

This program covers the most in-demand tools used by modern Data Scientists and AI Engineers.

Data Science Tools

Pre Requisite

  • Basic computer knowledge
  • No prior programming experience required
  • Willingness to learn and practice
  • Internet-enabled system

Description

This comprehensive program is designed to take you from beginner to advanced in Data Science and AI. You will learn how to analyze data, build machine learning models, and deploy them into production environments using modern tools and frameworks.

The course goes beyond theory, focusing heavily on:

  • Practical oriented
  • Real-time use cases
  • Industry-relevant tools
  • End-to-end project implementation

By the end of the program, you will be able to:

  • Build intelligent systems using ML & AI
  • Work with large-scale data pipelines
  • Develop and deploy production-ready models
  • Apply Generative AI techniques in real scenarios

Course Curriculum

Module 1: Programming & Python Foundations
  • Python basics, variables, data structures
  • Functions, OOP, exception handling
  • File handling, threading, web scraping
Module 2: Data Analysis & Processing
  • NumPy, Pandas
  • Data preprocessing
  • Date-time handling
Module 3: Statistics & Probability
  • Descriptive & inferential statistics
  • Hypothesis testing, confidence intervals
  • Bayes theorem, distributions
Module 4: Machine Learning
  • Regression (Linear, Polynomial, Ridge, Lasso)
  • Classification techniques & evaluation metrics
  • Bias-variance, cross-validation
Module 5: Advanced Machine Learning
  • Decision Trees, Random Forest
  • XGBoost, LightGBM
  • Clustering (K-Means, DBScan)
  • PCA & anomaly detection
Module 6: Time Series
  • ARIMA, SARIMA
  • Forecasting techniques
Module 7: NLP
  • Text preprocessing, TF-IDF, N-grams
  • Sentiment analysis
  • Text summarization

Download Course Curriculum

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Instructor

Principal Data Scientist

  • Industry experience in AI & ML systems
  • Hands-on expertise in real-world deployments
  • Focus on practical, job-ready learning

Candidate Review Videos

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Additional Demo Sessions

Candidates receive additional demo sessions and regular tasks.


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