Data Science

Data Science

12 Weeks
5 Projects
Beginner to Intermediate
$999

Course Overview

Learn to extract insights from data using statistical analysis, visualization, and machine learning techniques

The Data Science course is designed for individuals who want to learn how to analyze and interpret complex data to make informed decisions. This comprehensive program covers the entire data science workflow, from data collection and cleaning to analysis and visualization.

You'll learn how to use Python and its powerful libraries for data manipulation, statistical analysis, and machine learning. Through hands-on projects, you'll develop the skills to extract meaningful insights from data and communicate your findings effectively.

By the end of this course, you'll have a solid foundation in data science principles and techniques, enabling you to tackle real-world data challenges and make data-driven decisions.

What You'll Learn

Key topics covered in this course

Data Analysis with Python
Statistical Methods
Data Visualization
Machine Learning for Data Science
Big Data Processing
Data Engineering Basics
Business Intelligence

Course Content & Information

Detailed curriculum and request more information

Data Science

Module 1: Introduction to Data Science

  • What is Data Science?
  • The Data Science Workflow
  • Setting Up Your Data Science Environment
  • Python for Data Science
  • Project: Exploratory Data Analysis

Module 2: Data Manipulation and Analysis

  • Data Structures in Python
  • NumPy for Numerical Computing
  • Pandas for Data Manipulation
  • Data Cleaning and Preprocessing
  • Project: Data Cleaning and Transformation

Module 3: Data Visualization

  • Principles of Data Visualization
  • Matplotlib for Basic Plotting
  • Seaborn for Statistical Visualization
  • Interactive Visualizations with Plotly
  • Project: Creating a Data Dashboard

Module 4: Statistical Analysis

  • Descriptive Statistics
  • Probability Distributions
  • Hypothesis Testing
  • Correlation and Regression
  • Project: Statistical Analysis Report

Module 5: Machine Learning Fundamentals

  • Introduction to Machine Learning
  • Supervised Learning Algorithms
  • Unsupervised Learning Algorithms
  • Model Evaluation and Validation
  • Project: Building a Predictive Model

Module 6: Big Data and Data Engineering

  • Introduction to Big Data
  • Data Storage Solutions
  • SQL for Data Science
  • Introduction to Spark
  • Project: Working with Large Datasets

Module 7: Business Intelligence and Applications

  • Data-Driven Decision Making
  • Business Intelligence Tools
  • Creating Reports and Dashboards
  • Communicating Data Insights
  • Project: Business Intelligence Dashboard
Data Science Projects

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