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📈 Data Science & Analytics

Extract meaningful insights from data and build intelligent systems that drive decision-making in the modern world.

🎯 Course Overview

Comprehensive data science course covering the entire pipeline from data collection to model deployment.

  • Duration: 16 weeks (4 credit hours)
  • Prerequisites: Basic programming and statistics
  • Languages: Python, R, SQL
  • Level: Intermediate to Advanced
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UNIVERSITY OF DELHI SYLLABUS

📘 Course Curriculum

Unit-wise syllabus aligned with the University of Delhi curriculum.

Unit 1: Introduction to Data Science

  • Data science lifecycle
  • Types of data
  • Tools and ecosystem

Unit 2: Data Wrangling and EDA

  • Data cleaning and transformation
  • Handling missing values
  • Exploratory data analysis with pandas

Unit 3: Statistics and Probability

  • Descriptive statistics
  • Probability distributions
  • Hypothesis testing

Unit 4: Data Visualization

  • Principles of visualization
  • Matplotlib and Seaborn
  • Storytelling with data

Unit 5: Machine Learning and Big Data

  • Supervised and unsupervised learning
  • Model evaluation
  • Introduction to big data tools

🛠️ Tools & Technologies

Industry-standard tools and platforms for data science:

  • Python: NumPy, Pandas, Scikit-learn, TensorFlow
  • Visualization: Matplotlib, Seaborn, Plotly
  • Big Data: Apache Spark, Hadoop
  • Cloud: AWS, Azure, Google Cloud
  • Databases: SQL, MongoDB, Redis
  • MLOps: Docker, Kubernetes, MLflow

🎯 Learning Outcomes

Upon completion, students will be able to:

  • Master the complete data science workflow
  • Implement machine learning algorithms
  • Create compelling data visualizations
  • Process big data using distributed computing
  • Deploy models in production environments
  • Communicate insights to stakeholders

📊 Assessment Methods

Project-based evaluation emphasizing real-world applications:

  • Lab Assignments (35%): Hands-on data projects
  • Course Projects (30%): Real-world case studies
  • Mid-term Exam (15%): Theoretical concepts
  • Final Project (20%): Capstone project

🌟 Career Opportunities

Prepare for high-demand data science roles:

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Research Scientist
  • Product Manager (Data)
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🚀 Industry-Aligned Curriculum

This comprehensive data science course is built around industry partnerships and real-world datasets. Explore the modules and resources below to get started.