talk-data.com

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:00 am - 10:05 am Arrival, socializing, and Opening (PDT) 10:05 am - 12:00 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:00 pm - 12:10 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Webinar Passcode 325997

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:00 am - 10:05 am Arrival, socializing, and Opening (PDT) 10:05 am - 12:00 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:00 pm - 12:10 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Webinar Passcode 325997

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:00 am - 10:05 am Arrival, socializing, and Opening (PDT) 10:05 am - 12:00 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:00 pm - 12:10 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Webinar Passcode 325997

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:00 am - 10:05 am Arrival, socializing, and Opening (PDT) 10:05 am - 12:00 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:00 pm - 12:10 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/9617152905708/WN_Nv0aUvB1T-W6oQ22HtSjZA

Webinar Passcode 325997

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/5916962723955/WN_st72tpxLSWirzy1ndwEKmQ

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:25 am - 10:30 am Arrival, socializing, and Opening (PDT) 10:30 am - 12:20 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:20 pm - 12:30 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/5916962723955/WN_st72tpxLSWirzy1ndwEKmQ

Webinar Passcode 938275

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/5916962723955/WN_st72tpxLSWirzy1ndwEKmQ

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

(PDT) 10:25 am - 10:30 am Arrival, socializing, and Opening (PDT) 10:30 am - 12:20 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" (PDT) 12:20 pm - 12:30 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/5916962723955/WN_st72tpxLSWirzy1ndwEKmQ

Webinar Passcode 938275

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2416948019759/WN_VT4mYaqaR96iJhak0RjKCw

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

10:25 am - 10:30 am Arrival, socializing, and Opening 10:30 am - 12:20 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" 12:20 pm - 12:30 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2416948019759/WN_VT4mYaqaR96iJhak0RjKCw

Webinar Passcode 474616

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2416948019759/WN_VT4mYaqaR96iJhak0RjKCw

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

10:25 am - 10:30 am Arrival, socializing, and Opening 10:30 am - 12:20 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" 12:20 pm - 12:30 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2416948019759/WN_VT4mYaqaR96iJhak0RjKCw

Webinar Passcode 474616

Dr. Yasin Ceran presents a comprehensive workshop on time series forecasting models and techniques.

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis

Module 2: Exploratory Data Analysis for Time Series

Module 3: Traditional Time Series Forecasting Models

Module 4: Advanced Time Series Forecasting Models

Module 5: Model Evaluation and Selection

Module 6: Handling Seasonality and Trends

Prerequisites:

* Familiarity with the Jupiter Notebooks interface

* Basic understanding of foundational statistical techniques

* Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

10:25 am - 10:30 am Arrival, socializing, and Opening

10:30 am - 12:20 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques"

12:20 pm - 12:30 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Webinar Passcode 175691

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

7:45 pm - 7:50 pm Arrival, socializing, and Opening 7:50 pm - 9:45 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop" 9:45 pm - 9:50 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

2:45 pm - 2:50 pm Arrival, socializing, and Opening 2:50 pm - 4:45 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" 4:45 pm - 4:50 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Immersive workshop on time series analysis and forecasting using Python, covering introduction to time series analysis, exploratory data analysis, traditional and advanced forecasting models, evaluation and model selection, and handling seasonality and trends.

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

2:45 pm - 2:50 pm Arrival, socializing, and Opening 2:50 pm - 4:45 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" 4:45 pm - 4:50 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

7:45 pm - 7:50 pm Arrival, socializing, and Opening 7:50 pm - 9:45 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop" 9:45 pm - 9:50 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg

Time series forecasting plays a crucial role in machine learning, requiring special attention to capture the impact of time-related components such as trends and seasonality. Join us in this immersive workshop where we will delve into the depths of time series analysis and forecasting using Python.

Workshop Curriculum:

Module 1: Introduction to Time Series Analysis Module 2: Exploratory Data Analysis for Time Series Module 3: Traditional Time Series Forecasting Models Module 4: Advanced Time Series Forecasting Models Module 5: Model Evaluation and Selection Module 6: Handling Seasonality and Trends

Prerequisites: * Familiarity with the Jupiter Notebooks interface * Basic understanding of foundational statistical techniques * Proficiency in data reading and preprocessing tasks, including data cleaning using Python

Agenda:

2:45 pm - 2:50 pm Arrival, socializing, and Opening 2:50 pm - 4:45 pm Dr. Yasin Ceran, "Mastering Time Series Forecasting with Python A Comprehensive Workshop on Forecast Models and Techniques" 4:45 pm - 4:50 pm Q&A

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

https://us02web.zoom.us/webinar/register/2516878103582/WN_5afkkgtBQlK6wEYlAlW2Jg