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Big Data Analytics/Data Science Group 1
Big Data Analytics/Data Science Group 1
127 Students enrolled
Created by: Arta Abdullahu
Last Updated: 8th March 2024
Shqip (Albanian)
Requirements
Big Data Analytics/Data Science Group 1
Description
Big Data Analytics/Data Science Group 1
Content
Chapter 1 - Introduction to Data Science
The Foundations of Data Science
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Training and implementation of practical exercise on Big Data Analytics group 1
Chapter 2 - Foundations of Data Science
The Data Science Pipeline| Role of Data Scientists
Applications of Data Science| Data Science Tools and Technologies| Data Science Ethics and Privacy| Challenges and Opportunities
Case Studie| Future Trends in Data Science| Data Collection and Preprocessing
Chapter 3 - Exploratory Data Analysis (EDA)
Exploratory Data Analysis (EDA)| Statistical Foundations| Big Data and Data Warehousing| Quiz
Chapter 4 - Big Data Infrastructure and Technologies
Data Transmission Analysis| Data Warehouse| Data Pipeline| Big Data Analysis Techniques| Data Mining Process| Correlation/Regression| Natural Language Processing (NLP)| DP
Applications of data science: case study, fraud detection why do we need Machine Learning in this rsat study? Using artificial intelligence to enhance smartwatch performance IOT (internet of
Managing Data: Techniques, Practices, and Applications|Quiz
Statistical Significance and Forecasting Temporal Services| Statistical Significance| Forecasting Model and Temporal Service Data| Case Study: Customer Subscription Prediction| Clustering|
Chapter 5 - Big Data Analysis with Excel
Introduction to Big Data Analysis with Excel| Handling Large Datasets in Excel| Advanced Data Analysis Techniques| Data Visualization and Reporting
Advanced Data Analysis Techniques| Data Visualization and Reporting
Chapter 6 - Python for Beginners
Introduction to Python|Overview of Python and its features.|Setting up Python environment (installation, IDEs).|Writing and executing your first Python program.
Basic Python Concepts|Variables and data types (integers, floats, strings, booleans).|Basic arithmetic and string operations.Understanding and using Python's built-in functions.|Introduction
Control Flow and Functions|Conditional statements (if, elif, else).|Introduction to logical operators (and, or, not).|ntroduction to loops (for loops, while loops).|Writing and using function
Control Flow and Functions|Conditional statements (if, elif, else).|Introduction to logical operators (and, or, not).|ntroduction to loops (for loops, while loops).|Writing and using function
Data Structures|Lists: Creating, accessing, and modifying lists.|Tuples: Understanding tuple syntax and immutability.|Dictionaries: Creating and accessing key-value pairs.|Sets: Introduction
Data Structures|Lists: Creating, accessing, and modifying lists.|Tuples.|Dictionaries| Tasks
Data Structures|Lists: Creating, accessing, and modifying lists.|Tuples.|Dictionaries| Tasks
Chapter 7 - Python for Data Analysis
Python Pandas DataFrame| DataFrame from dict of ndarray/lists: | Dealing with Rows and Columns| Indexing and Selecting Data| Working with Missing Data| Iterating over rows and columns
Python Pandas DataFrame| DataFrame from dict of ndarray/lists: | Dealing with Rows and Columns| Indexing and Selecting Data| Working with Missing Data| Iterating over rows and columns
Form Manipulation with CSV Library in Python
Reading CSV Files with Pandas| Reading Json Files with Pandas
Dataframe Manipulations | Class Tasks for Dataframe Manipulations
Pandas - Analyzing DataFrames
Data Cleaning - Real Examples
Data Cleaning - Real Examples
Project Big Data and Quiz
Chapter 8 - Introduction to Data Visualization
Basic Plotting with Matplotlib| Scatter Plots and Bar Charts
Histograms and Density Plots| Advanced Plotting Techniques| Data Visualization Best Practices| Real-World Applications|
Chapter 9 - SQL for Big Data
Introduction basic SQL concepts and commands.
The Evolution of SQL in Big Data| SQL Technologies for Big Data|
Setting Up a Big Data SQL Environment| Basic SQL Queries in Big Data
Basic SQL Queries in Big Data
Advanced SELECT Statements| Subqueries and Nested Queries:| Common Table Expressions (CTEs)
Essential SQL for Data Science| Data Cleaning and Transformation with SQL
Exploratory Data Analysis (EDA) with SQL| Feature Engineering with SQL
Case Studies and Real-World Applications| QUIZ
Chapter 10 - Power BI
Power BI Dashboards and Reports
Data Modeling in Power BI, Data Visualization with Power BI
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