Time Series Analysis:Hands-On Projects & Advanced Techniques

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Temotec Learning Academy

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1. Introduction

1. Introduction.mp4

04:09

2. Jupyter Shortcuts.html

3. Understanding Data Types and Structures in Python..mp4

10:19

4. Understanding Python Data Structure Wrap up..mp4

04:45

2. Python Refresher

1. String Functions in Python Part 1.mp4

02:53

2. String Functions in Python Part 2.mp4

01:38

3. String Functions in Python Part 3.mp4

02:06

4. String Functions in Python Part 4.mp4

01:18

5. String Functions in Python Part 5.mp4

6. Lists..mp4

04:21

7. Tuples..mp4

02:29

8. Sets..mp4

05:32

9. Dictionaries..mp4

04:48

10. Control Flow IF..mp4

04:13

11. For Loop Part 1..mp4

02:44

12. For Loop Part 2..mp4

05:01

13. While Loop Part 1..mp4

05:14

14. While Loop Part 2..mp4

03:34

15. While Loop Best Practices..mp4

02:48

16. Introduction to Functions in Python..mp4

02:18

17. Functions in Python and Arguments..mp4

02:16

18. Function Tips & Tricks Recursion..mp4

02:15

19. Function Tips & Tricks Functions Decorators and Higher Order Functions..mp4

02:24

20. Functions Tips & Tricks Lambda Functions..mp4

02:00

21. Function Tips & Tricks Functions Caching & Memoization..mp4

03:44

22. Error Handling in Python..mp4

01:06

23. Files and Modules in Python..mp4

06:52

3. Object Oriented Programming (OOP) In Python Refresher

1. Creating Simple Class..mp4

06:26

2. Overviewing Constructor..mp4

16:53

3. Learning How to creating Dunder Methods.mp4

05:27

4. Learning about Inheritance..mp4

06:43

5. Knowing What is the Encapsulation.mp4

03:28

6. Learning also about Multiple Inheritance..mp4

04:12

7. Knowing What is the Overriding.mp4

05:04

8. Learning about Decorators..mp4

05:02

9. Learning How to use Build-in Decorators.mp4

05:44

4. Project 1 Python Pandas + PostgreSQL

1. PostgreSQL Downloading & Installing..mp4

03:07

2. Create Database..mp4

01:09

3. Restore Database..mp4

01:13

4. Using CMD & Python pip.PyPi to Install Jupyter Lab & Pandas..mp4

01:56

5. Create a CSV File Using PostgreSQL.mp4

09:26

6. Fetchmany and Fetchall.mp4

03:00

7. Runnig SQL Query Using Python Panadas Module..mp4

05:00

8. Using Python Pandas Package to load PostgreSQL the Data Output file..mp4

09:26

9. Data Analysis Process Overview..mp4

03:06

10. Pandas Methods..mp4

05:16

11. Pandas data visualization..mp4

09:01

12. Pandas Data Analysis..mp4

04:03

13. Sampling Error..mp4

04:00

5. Project 2 Scrape the Web & Saving Data to a Database

1. How to Scrape a website.mp4

13:23

2. Scrape a Table inside a Webpage using Pandas and LXML Python Modules!.mp4

05:00

3. Visualization of the Scarped Data..mp4

06:00

4. Save The Scraped Data to a Database..mp4

07:16

6. Project 3 Python Automation AFC (OS Python Module)

1. Download & Install of Sublime Text Editor..mp4

02:02

2. Project Walkthrough..mp4

03:00

3. Project Arrange Folder Content..mp4

09:14

7. Project 4 Python Automation Project MPF (PyPDF2 Python Module)

1. Project Walkthrough..mp4

02:00

2. Project Solution..mp4

07:00

8. Project 5 Python Automation Business Email List (smtplib Python Module)

1. Part 1.mp4

03:00

2. Part 2.mp4

16:15

3. Part 3.mp4

22:00

9. Python Numpy Library

1. Numpy Intro..mp4

01:44

2. Numpy.shape & Numpy.size.mp4

10:12

3. Creating Numpy nd arrays using Numpy functions..mp4

08:33

4. Numpy.unique( ) & Array slicing..mp4

04:03

5. Numpy Calculations and Operators..mp4

08:24

6. Numpy Aggregations..mp4

06:03

7. Numpy Reshape and Transposing..mp4

09:16

8. Comparing Numpy Arrays..mp4

07:05

9. Numpy Arrays Images Processing..mp4

05:32

10. Accessing, Manipulating & Filtering DataFrames

1. Data manipulation using DataFrames..mp4

06:17

2. Accessing Data Using DataFrames..mp4

06:27

3. Data aggregation and summarization..mp4

07:28

4. Create New Columns, Drop Unnecessary Ones, and Perform Various Data Manipulation.mp4

06:36

5. Essential Techniques for Peeking at & Describing our Data in Python..mp4

06:59

6. Filtering Data..mp4

07:16

11. Data Visualization in Python

1. Introduction to Data Visualization in Python..mp4

04:38

2. Histograms a Powerful Tool for Visualizing the Distribution of Data..mp4

07:25

3. Visualizing Trends using a Real-World Financial Data..mp4

04:46

4. Determining and Choosing the Appropriate Plot Type..mp4

07:49

12. Time Series Data Analysis using Python

1.1 benchmark data.csv

1.2 financial data.csv

1. Datasets used in this Section..html

2. Introduction to Time Series Analysis..mp4

05:33

3. Creating, Converting Datetimes from Strings & Manipulating Datetime Data..mp4

04:27

4. Accessing Datetime Attributes, Comparing Datetimes, & Making Relative Datetime..mp4

05:07

5. Understanding Time Series Growth Rates & Comparing Stock Prices with a Benchmark.mp4

04:42

6. Changing Time Series Frequency By Up-Sampling & Interpolation..mp4

04:06

7. Changing Time Series Frequency By Down-Sampling..mp4

03:46

8. Window Functions in Time Series Analysis..mp4

06:39

9. Stocks Prices Series Analysis with Lags..mp4

03:32

13. Project 6 Time Series Analysis of Betcoin Historical Data dataset

1. Introduction to this Project..mp4

04:38

2. Data Preprocessing and Cleaning..mp4

02:47

3. Visualizing Time Series Data..mp4

03:27

4. Creating Forecasting Models..mp4

07:19

5. Predicting Future Bitcoin Prices..mp4

06:07

14. Bonus

1. Thanks.html

Description

Hands-On Time Series with Python: Accessing, Manipulating, Visualizing Data, Master Advanced Techniques & Build Projects

What You'll Learn?

Import and clean time series data.
Calculate common time series statistics.
Create time series visualizations.
Build time series models.
Forecast time series data.
Accessing, Manipulating, Visualizing Data.
Build Projects.

Who is this for?

Beginners and intermediate Python programmers.

Students want to apply Python knowledge through Python Projects.

Students want to build the skills that is needed to become a Python Scripting Guru.

Data analysts & Data scientists.

Business analysts.

AI Engineers.

Financial Analysts.

Anyone who wants to learn how to analyze time series data.

What You Need to Know?

No prior knowledge is required. So whether you're new to Python or have some programming experience.

Computer and internet.

Everything else you need to learn Python Time Series Data Analysis is already in this course.

Welling to learn advanced Techniques.

More details

Description
Time series analysis focuses on data collected over time, like stock prices, weather patterns, or sensor readings. It reveals hidden trends, patterns, and relationships within this data. By understanding these patterns, we can predict future values, make informed decisions, and gain insights into complex phenomena. Time series analysis is a powerful tool for various fields, including finance, economics, healthcare, and environmental science.
This course will teach you how to use Python to analyze time series data. You will learn how to:
Import and clean time series data.
Calculate common time series statistics.
Create time series visualizations.
Build time series models.
Forecast time series data.
Accessing, Manipulating, Visualizing Data.
Master Advanced Techniques.
Build Projects.
Whether you're new to Python or have some programming experience, this course welcomes you to the world of time series analysis. No prior knowledge is required, as we'll start from the basics and gradually introduce advanced techniques using Python.

Who this course is for:
Beginners and intermediate Python programmers.
Data analysts.
Data scientists.
Business analysts.
Anyone who wants to learn how to analyze time series data.
AI Engineers.
Financial Analysts.
Requirements:
No prior knowledge is required. So whether you're new to Python or have some programming experience.
A computer with Python installed.
Welling to learn advanced Techniques.
Who this course is for:
Beginners and intermediate Python programmers.
Students want to apply Python knowledge through Python Projects.
Students want to build the skills that is needed to become a Python Scripting Guru.
Data analysts & Data scientists.
Business analysts.
AI Engineers.
Financial Analysts.
Anyone who wants to learn how to analyze time series data.

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Hello there! With over 350,000 happy students enrolled in my courses, I'm thrilled to be sharing my programming and data science expertise with you.As a programmer and data scientist, I've mastered several programming languages, including Python, SQL, JavaScript, R Programming, as well as tools like Excel, Tableau, Jupyter Notebook, Apache Cassandra, Apache Spark, Apache Airflow, Apache Kafka, AWS, and R Studio. I'm passionate about teaching and sharing my knowledge with the community.When I'm not coding, you can usually find me hiking or reading a good book. I believe that lifelong learning is essential for personal development, and my courses are designed to encourage students to continue learning outside of formal education.I update my courses every month to add new sections based on your feedback and requests. So don't wait – enroll in my courses now and start your journey towards mastering programming, web development, data science, data Engineering and Machine Learning!

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