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Big Data Analytics/Data Science Group 2
Big Data Analytics/Data Science Group 2
127 Students enrolled
Created by: Freda Dyrkaj
Last Updated: 5th March 2024
English
Requirements
Big Data Analytics/Data Science Group 2
Description
Big Data Analytics/Data Science Group 2
Content
1- Introduction
1- Introduction to Data Science
2- Introduction to Python Language
2- Programming Concepts
3- If-Else Statements-Functions
4- String Variables
5- Lists Variables
6-Dictionaries
7-Tuples-Files
8- Exercises
9-First Exam_Python
3 - Data Wrangling With Pandas
10- Introduction Pandas
11-Exercises
12-Data Cleaning with Pandas
4- Introduction to Analytics and Visualization
13-Introduction to Analytics
14-NumPy Exercises
15-NumPy Visualization
16-Project_MatplotLib
5- Advanced Analytics
17-SecondExam-Pd,Np,Plt Libraries. Introduction to Advanced Analytics
18- Linear Regression
19- Multiple Regression
20-Logistic Regression
21- LogReg Exercises, Visualization
22-Project Nr1_Presentation
23-Scaling Data Analytics
24- Predictive Modeling and Analytics
25- Third Exam_Regression
6- Introduction to SQL
26- Introduction to DBMS
27- Introduction to MongoDb-Hadoop-Data Mining
28- Relational Model
29- MySQL_QUERY
30- MySql Constraints
31- MySql Select-Where/Exercises
32- MySql- Index_View_Data
33- MySql- Joins
34- MySql- Group By/Having by
35- MySql- Stored Procedures
36- MySql-Exercises total lessons
37- Mysql Exam
7- Using Databases in Python
38- Python connect with MySql
39- Python MySql Exercises
40- Functions and Queries in PythonMysql
41- Exercises, Repeat Lessons
8- Supervised Learning
42- Introduction to KNN Algorithm
44- KNN Algorithm-Regression
45- KNN Algorithm-Classifier
46- KNN Classifier Vs Regression
49- Unsupervised learning
47- Statistical Tests
51- Exam Supervised Learning
43- KNN-Exercises
48- P-value
9- UnSupervised Learning
50- KMeans Cluster
52- KMeans Exercises
53- Silhouette score
54- Supervised vs Unsupervised Learning
55- Hierarchical Clustering
56- Hierarchical Clustering-Exercises
10- Repeat
59- Repeat All Chapters
60- Final Exam
57- Project Presentation
61- Project Presentation
62- Project Presentation
63- Student discuss-Report preparation
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