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Big Data Analytics/ Data Science
Big Data Analytics/ Data Science
69 Students enrolled
Created by: Arta Abdullahu
Last Updated: 27th September 2023
English
Requirements
Big Data Analytics/ Data Science
Description
Big Data Analytics/ Data Science
Content
Chapter 1 - Introduction to Data Science
The Foundations of Data Science
Data science process and lifecycle
The roles of data scientists, data analysts, data engineers, and database administrators
Preparation, Exploration, and Visualization|Data Science: Theories, Models and Analytics
Data Collection and Storage
Experimentation and Prediction
The Data Ecosystem
Data Science vs. Data Analytics: Understanding the Differences| Predictive Modeling and Analytics
4 big Vs of Big Data: volume, velocity, variety, and veracity| Data Science at Scale
Chapter 2 - Python Programming Fundamentals
Introduction to Python Language
Control Flow(Conditional statements (if, elif, else) Loops (for, while) Iteration and looping techniques Control flow with Python)
Data Structures(Lists and their operations Tuples Sets Dictionaries Basic operations on data structures)
Functions (Defining and calling functions Function parameters and return values Scope and lifetime of variables Built-in functions and modules)
Data Structures(Lists and their operations Tuples Sets Dictionaries Basic operations on data structures)_Advaced
Functions and Modules
Dictionaries and Sets(Understanding dictionaries and sets. Operations on dictionaries and sets. Use cases for each data structure.)
Dictionaries and Sets_Adv
Chapter 3 - Python for Data Analysis
Python File Open and Write
Python File Open and Write Part 2
Matplotlib Plotting
Matplot Subplot, Scatter Advanced
Matplot libraries - Part 2
Managing Big Data using Apache Hadoop and MongoDB
Working with large CSV files in Python
Working with large CSV files in Python_Part 2
Chapter 4 - SQL for Big Data
Introduction to SQL
Data Manipulation and Analysis with SQL and Big Data: Complex queries and transformations on large datasets
Data Manipulation and Analysis with SQL and Big Data: Complex queries and transformations on large datasets
Advanced Topics in SQL and Big Data: Window functions and analytics in SQL Working with semi-structured and unstructured data Handling streaming data and real-time analytics Data governance a
Chapter 5 - Optimization and Causal Mechanistic Analysis
Introduction to Optimization: Overview of optimization concepts and terminology Different types of optimization problems (linear, nonlinear, integer, etc.) Mathematical modeling and formulati
Linear Programming, Nonlinear Programming, Integer Programming, Causal Mechanistic Analysis
Chapter 6 - Analyze Data in Excel
Excel Basics for Data Analysis
Advanced Data Analysis Tools, PivotTables and PivotCharts
Chapter 7 - Power BI
Introduction to Power BI
Data Modeling in Power BI, Data Visualization with Power BI
Power BI Dashboards and Reports
Chapter 8 - Architecture for Big Data and Data Engineering
Data Storage and Management, Stream Processing and Real-time Analytics, Data Integration and ETL Processing
Data Warehousing and Analytics
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Arta Abdullahu
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