Complete Time Series Analysis for Data Science | Data Analysis | Full Crash Course | Statistics

📈 Complete Time Series Analysis eBook + Python Notebook (Written by me covering all topics): https://topmate.io/ayushi_mishra/1229949 Master Time Series Analysis for Data Science & Data Analysis in 3 hours. This comprehensive Crash Course covers EVERYTHING you need to know, from Stationarity, Forecasting models to Time series data preprocessing. Whether you're a complete beginner or looking for a refresher, this video is your one-stop shop for conquering Data Science Time Series Analysis! All topics are implemented using Python ➖➖➖➖➖➖➖➖➖➖➖➖ 👍 Subscribe for more Data Science content: https://bit.ly/48MFgCf 🔥 Book 1:1 call with me (Career Guidance, Resume Review, LinkedIn Profile Review) : https://topmate.io/ayushi_mishra/133733 ➖➖➖➖➖➖➖➖➖➖➖➖➖ ✅ 7+Data Analysis Portfolio Ready Projects Resources: https://topmate.io/ayushi_mishra ➖➖➖➖➖➖➖➖➖➖➖➖➖ ✅ Job Preparation and Interview Guide: https://topmate.io/ayushi_mishra/842027 ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: https://www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram: https://www.instagram.com/techie.data/ Timestamps: 00:00 Complete Syllabus and importance of time series analysis 11:06 Ebook and Python Notebook Introduction 11:55 Time Series Data 14:49 Time Series Data Characteristics 18:18 Time Series Analysis 22:31 Time Series Decomposition 30:02 Additive and Multiplicative Decomposition methods 33:48 Classical Decomposition 37:35 STL Decomposition using LOESS 38:49 Difference between STL and classical decomposition 42:15 STL decomposition using Python 43:31 Stationarity in Time series 45:28 Why do we need stationary time series data? 49:03 Weak Stationary and Strict Stationary 57:05 Testing for stationarity 57:39 Augmented Dickey-Fuller (ADF) test 1:00:12 Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test 1:03:29 Kolmogorov–Smirnov test (K–S test or KS test) 1:11:15 Non stationary data to stationary data 1:11:34 Differencing 1:14:00 Transformation 1:15:24 Logarithmic Transformation | Power Transformation | Box Cox Transformation 1:16:41 Detrending and seasonal adjustment 1:28:07 White Noise and Random Walk 1:35:28 Time Series Forecasting Models 1:37:19 Autoregressive (AR) 1:41:20 Moving Average (MA) 1:46:14 Autoregressive Moving Average (ARMA) 1:48:10 Autoregressive Integrated Moving Average (ARIMA) 1:51:01 Seasonal Autoregressive Integrated Moving Average (SARIMA) 1:54:51 Vector AutoRegressive (VAR) | Vector Moving Average (VMA) | Vector AutoRegressive Moving Average (VARMA) | Vector AutoRegressive Integrated Moving Average (VARIMA) 1:55:37 Granger causality test 1:57:31 Time Series Forecasting using Python 2:07:58 Smoothing Methods 2:10:00 Moving Average (Simple, Weighted, Exponential) 2:14:44 Exponential Smoothing 2:20:46 Autocorrelation (ACF) and Partial Autocorrelation Function (PACF) 2:28:15 Identifying models from ACF and PACF 2:34:47 Model evaluation metrics 2:34:54 Mean Absolute Error (MAE) 2:36:41 Mean Squared Error (MSE) 2:38:12 Root Mean Squared Error (RMSE) 2:38:44 Mean Absolute Percentage Error (MAPE) 2:39:41 Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) 2:43:19 Time series data preprocessing 2:48:28 Resampling 🔗 Check out these other useful videos: Data Analyst Roadmap: https://youtu.be/MKncxvvRJXM Data Analysis Project using Python: https://youtu.be/obJZ1rB7TKc Python vs R: Which is best for career? : https://youtu.be/BWqDEB3hvRY Data Analysis Project using Python and SQL: https://youtu.be/LcMjsqZiSjY Relevant Keywords: Time series analysis Time series forecasting Time series analysis in statistics Time series statistics Time series forecasting python Time series analysis python Time series forecasting machine learning Time series analysis for data science Time series analysis for data analyst Stock price prediction Stock price prediction using python Stock price prediction using machine learning Data Analyst Data Analytics Data Analyst Project Data Analysis project Data Science Data Science project Data Analysis project for beginners Data Science project for beginners Data analysis using python Data Science using python Python Python programming