Data Science – (Excel, PowerBi, SQL & Python)

Categories: Data Science
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What Will You Learn?

  • • Introduction to Data Analysis
  • • Data Analysis Example A
  • • Data Analysis Example B
  • • How to use Jupyter Notebooks Intro
  • • Jupyter Notebooks Cells
  • • Jupyter Notebooks Importing and Exporting Data
  • • Numpy Introduction A
  • • Numpy Introduction B
  • • Numpy Arrays
  • • Numpy Boolean Arrays
  • • Numpy Algebra and Size
  • • Pandas Introduction
  • • Pandas Indexing and Conditional Selection
  • • Pandas DataFrames
  • • Pandas Conditional Selection and Modifying DataFrames
  • • Pandas Creating Columns
  • • Data Cleaning Introduction
  • • Data Cleaning with DataFrames
  • • Data Cleaning and Visualizations
  • • Reading Data Introduction
  • • Reading Data CSV and TXT
  • • Reading Data from Databases
  • • Parsing HTML and Saving Data
  • • Python Introduction
  • • Python Functions and Collections
  • Python Iteration and Modules

Course Content

Module 1 – Introductory
What is Data Science? Data Science is about data gathering, analysis and decision-making. Data Science is about finding patterns in data, through analysis, and make future predictions. By using Data Science, companies are able to make: Better decisions (should we choose A or B) Predictive analysis (what will happen next?) Pattern discoveries (find pattern, or maybe hidden information in the data) Where is Data Science Needed? Data Science is used in many industries in the world today, e.g. banking, consultancy, healthcare, and manufacturing. Examples of where Data Science is needed:

EXCEL

PowerBi

Python Basic

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