Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
8 Hour(s) 40 Minute(s)
Language
English
Taught by
Temotec Learning Academy
Rating
3 views
Course Overview
Hands-On Time Series with Python: Accessing, Manipulating, Visualizing Data, Master Advanced Techniques & Build Projects
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.
Course Content
- 10 section(s)
- 100 lecture(s)
- Section 1 Introduction
- Section 2 Python Refresher
- Section 3 Object Oriented Programming (OOP) In Python Refresher.
- Section 4 Project 1: Python Pandas + PostgreSQL
- Section 5 Project 2: Scrape the Web & Saving Data to a Database.
- Section 6 Project 3: Python Automation AFC (OS Python Module).
- Section 7 Project 4: Python Automation Project MPF (PyPDF2 Python Module).
- Section 8 Project 5: Python Automation Business Email List (smtplib Python Module).
- Section 9 Python Numpy Library.
- Section 10 Accessing, Manipulating & Filtering DataFrames.
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.
Reviews
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MMason Wright
I learned how to tidy up, prepare, and show time series data in a way that is easy to understand.This made ideas like ARIMA, SARIMA, and exponential smoothing seem
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EErnest Lewis
This was exactly what I needed to connect what I learned with how to put it into practice. The practical projects helped me understand ideas that were previously unclear to me
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GGlenn Davis
What stands out is the clear and detailed way of explaining complex topics like seasonality, stationarity, and checking for auto-correlation. It's complicated but easy to understand.
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WWillie Green
Working on real projects really changed everything. Instead of only memorizing formulas, you create models step by step, like ARIMA, SARIMA, LSTM, and others. Essential for anyone who is serious about predicting future trends using time series data.
