Complete Python topics required for the Data Engineer role: https://t.iss.one/sql_engineer/70
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Data Engineers
Complete Python topics required for the Data Engineer role:
➤ 𝗕𝗮𝘀𝗶𝗰𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻:
- Python Syntax
- Data Types
- Lists
- Tuples
- Dictionaries
- Sets
- Variables
- Operators
- Control Structures:
- if-elif-else
- Loops
- Break & Continue try-except block…
➤ 𝗕𝗮𝘀𝗶𝗰𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻:
- Python Syntax
- Data Types
- Lists
- Tuples
- Dictionaries
- Sets
- Variables
- Operators
- Control Structures:
- if-elif-else
- Loops
- Break & Continue try-except block…
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SQL Query Execution Order
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https://www.linkedin.com/posts/sql-analysts_guys-this-sql-question-is-asked-in-many-activity-7213904258629267456-PfZf
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https://www.linkedin.com/posts/sql-analysts_guys-this-sql-question-is-asked-in-many-activity-7213904258629267456-PfZf
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Python road map
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https://www.linkedin.com/posts/sql-analysts_complete-roadmap-to-learn-python-for-beginners-activity-7214847272734363648-hSKY?
Like for more
👇👇
https://www.linkedin.com/posts/sql-analysts_complete-roadmap-to-learn-python-for-beginners-activity-7214847272734363648-hSKY?
Like for more
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Python — Using reduce()
The reduce() function is a powerful tool from Python's functools module. It allows you to apply a function cumulatively to the items of a sequence, from left to right, reducing the sequence to a single value
The reduce() function is a powerful tool from Python's functools module. It allows you to apply a function cumulatively to the items of a sequence, from left to right, reducing the sequence to a single value
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📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
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