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شروع دوره :
1402/5/15 پایان دوره :
1402/8/09
موضوع : فنی، مهندسی و صنعت-کامپیوتر دسته بندی :
دوره نوع دوره :
آنلاین-حضوری
اساتید :
+ 3
سخنرانان :
+ 1
جلسات
# 1 | عنوان
Excel
| تاریخ یکشنبه, 15 مرداد 1402 | توضیحات System design and familiarity with the basic concepts of database Exploring Data Entry and Editing Techniques Data Cleaning and manipulation, Data Validation Using Functions for Data Analysis What if and Scenario Analysis Data Visualization Creating a management dashboard | از ساعت 18:00 | تا ساعت 21:00 |
# 2 | عنوان
Excel
| تاریخ سه‌شنبه, 17 مرداد 1402 | توضیحات System design and familiarity with the basic concepts of database Exploring Data Entry and Editing Techniques Data Cleaning and manipulation, Data Validation Using Functions for Data Analysis What if and Scenario Analysis Data Visualization Creating a management dashboard | از ساعت 18:00 | تا ساعت 21:00 |
# 3 | عنوان
What is a good metric? How to define a metric? How to validate your results
| تاریخ یکشنبه, 22 مرداد 1402 | توضیحات The north star metric Metrics for different stages of user lifetime Metrics for different business models Metrics for different stages of a business Hypothesis testing Correlation analysis | از ساعت 18:00 | تا ساعت 21:00 |
# 4 | عنوان
What is a good metric? How to define a metric? How to validate your results
| تاریخ سه‌شنبه, 24 مرداد 1402 | توضیحات The north star metric Metrics for different stages of user lifetime Metrics for different business models Metrics for different stages of a business Hypothesis testing Correlation analysis | از ساعت 18:00 | تا ساعت 21:00 |
# 5 | عنوان
How to clean data? How to calculate metrics? How to manipulate data using python and pandas? How to use sql queries
| تاریخ یکشنبه, 29 مرداد 1402 | توضیحات Getting started with Python and Pandas Filtering and aggregating data Steps of data cleaning Writing sql queries | از ساعت 18:00 | تا ساعت 21:00 |
# 6 | عنوان
How to clean data? How to calculate metrics? How to manipulate data using python and pandas? How to use sql queries
| تاریخ سه‌شنبه, 31 مرداد 1402 | توضیحات Getting started with Python and Pandas Filtering and aggregating data Steps of data cleaning Writing sql queries | از ساعت 18:00 | تا ساعت 21:00 |
# 7 | عنوان
Data Visualization and Storytelling
| تاریخ یکشنبه, 05 شهریور 1402 | توضیحات crafting a story with data choosing effective visualizations delivering the story | از ساعت 18:00 | تا ساعت 21:00 |
# 8 | عنوان
Data Visualization and Storytelling
| تاریخ سه‌شنبه, 07 شهریور 1402 | توضیحات crafting a story with data choosing effective visualizations delivering the story | از ساعت 18:00 | تا ساعت 21:00 |
# 9 | عنوان
What is data engineering
| تاریخ یکشنبه, 12 شهریور 1402 | توضیحات Introduction to data engineering role From data to big data Relational and non-relational databases Data modeling and database design Data lake and data warehouse Data frameworks, tools and technologies | از ساعت 18:00 | تا ساعت 21:00 |
# 10 | عنوان
What is data engineering
| تاریخ سه‌شنبه, 14 شهریور 1402 | توضیحات Introduction to data engineering role From data to big data Relational and non-relational databases Data modeling and database design Data lake and data warehouse Data frameworks, tools and technologies | از ساعت 18:00 | تا ساعت 21:00 |
# 11 | عنوان
How to write data pipelines
| تاریخ یکشنبه, 19 شهریور 1402 | توضیحات Data extraction, transformation and loading (ETL) Data pipeline scheduling Data pipeline orchestration | از ساعت 18:00 | تا ساعت 21:00 |
# 12 | عنوان
How to write data pipelines
| تاریخ سه‌شنبه, 21 شهریور 1402 | توضیحات Data extraction, transformation and loading (ETL) Data pipeline scheduling Data pipeline orchestration | از ساعت 18:00 | تا ساعت 21:00 |
# 13 | عنوان
How to scale data pipelines
| تاریخ یکشنبه, 26 شهریور 1402 | توضیحات Data event sourcing Data batch streaming Data stream processing | از ساعت 18:00 | تا ساعت 21:00 |
# 14 | عنوان
How to scale data pipelines
| تاریخ سه‌شنبه, 28 شهریور 1402 | توضیحات Data event sourcing Data batch streaming Data stream processing | از ساعت 18:00 | تا ساعت 21:00 |
# 15 | عنوان
What is machine learning and how does it fit in our business
| تاریخ یکشنبه, 02 مهر 1402 | توضیحات Introduction to Machine Learning Machine Learning Model Lifecycle Tools for Machine Learning Supervised learning UnSupervised learning Jupyter Notebooks | از ساعت 18:00 | تا ساعت 21:00 |
# 16 | عنوان
What is machine learning and how does it fit in our business
| تاریخ سه‌شنبه, 04 مهر 1402 | توضیحات Introduction to Machine Learning Machine Learning Model Lifecycle Tools for Machine Learning Supervised learning UnSupervised learning Jupyter Notebooks | از ساعت 18:00 | تا ساعت 21:00 |
# 17 | عنوان
How to fit regression models and find patterns in our data
| تاریخ یکشنبه, 09 مهر 1402 | توضیحات Linear/Logistic regression models Cost function/Loss function Time Series Analysis Anomaly detection Dimension Reduction Techniques | از ساعت 18:00 | تا ساعت 21:00 |
# 18 | عنوان
How to fit regression models and find patterns in our data
| تاریخ سه‌شنبه, 11 مهر 1402 | توضیحات Linear/Logistic regression models Cost function/Loss function Time Series Analysis Anomaly detection Dimension Reduction Techniques | از ساعت 18:00 | تا ساعت 21:00 |
# 19 | عنوان
How to classify data and make predictions based on classes. You are not certain of classes? Clustering is your solution.
| تاریخ یکشنبه, 16 مهر 1402 | توضیحات Classification models When to use Tree-base models? Bagging/Boosting/ Models is better than model Clustering | از ساعت 18:00 | تا ساعت 21:00 |
# 20 | عنوان
How to classify data and make predictions based on classes. You are not certain of classes? Clustering is your solution.
| تاریخ سه‌شنبه, 18 مهر 1402 | توضیحات Classification models When to use Tree-base models? Bagging/Boosting/ Models is better than model Clustering | از ساعت 18:00 | تا ساعت 21:00 |
# 21 | عنوان
Is your model well designed? How to improve it? Recommendation, Every business problem.
| تاریخ یکشنبه, 23 مهر 1402 | توضیحات Feature engineering Bias/Variance Regularization Hyper parameter tunning recommendation | از ساعت 18:00 | تا ساعت 21:00 |
# 22 | عنوان
Is your model well designed? How to improve it? Recommendation, Every business problem.
| تاریخ سه‌شنبه, 25 مهر 1402 | توضیحات Feature engineering Bias/Variance Regularization Hyper parameter tunning recommendation | از ساعت 18:00 | تا ساعت 21:00 |
# 23 | عنوان
Is our modeling complete? A to Z of the ML project pipeline.
| تاریخ یکشنبه, 30 مهر 1402 | توضیحات Statical concepts Model Interpreting Error Analysis Machine learning project pipeline Introduction to Neural Networks | از ساعت 18:00 | تا ساعت 21:00 |
# 24 | عنوان
Is our modeling complete? A to Z of the ML project pipeline.
| تاریخ سه‌شنبه, 02 آبان 1402 | توضیحات Statical concepts Model Interpreting Error Analysis Machine learning project pipeline Introduction to Neural Networks | از ساعت 18:00 | تا ساعت 21:00 |
# 25 | عنوان
Final Project
| تاریخ سه‌شنبه, 09 آبان 1402 | توضیحات _ | از ساعت 18:00 | تا ساعت 21:00 |
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