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Machine Learning
8 Lessons
All Levels
What you'll learn
- Comprehensive understanding of machine learning algorithms and techniques
- Proficiency in building and training machine learning models
- Skills in evaluating and fine-tuning model performance
- Knowledge of feature engineering and data preprocessing techniques
- Ability to apply machine learning to real-world problems
- Experience with working on machine learning projects
- Understanding of model deployment and scalability considerations
- Familiarity with popular machine learning frameworks and libraries
Python Data Expert
19 Lessons
50 hours
All Levels
What you'll learn
1. Python Arithmetic
2. Basic Data Types
3. Variables
4. Lists
5. Tuples and Strings
6. Dictionaries and Sets
7. NumPy Arrays
8. Pandas DataFrames
9. Reading and Writing Data
10. Control Flow
11. Functions
12. List Comprehensions
13. Data Exploration and Cleaning
14. Working With Text Data
15. Preparing Numeric Data
16. Dealing With Dates
17. Merging Data
18. Frequency Tables
19. Pandas
20. NumPy
Data Visualization
5 Lessons
20 hours
All Levels
What you'll learn
Techniques for creating compelling data visualizations
Understanding of best practices in data visualization
Proficiency in using data visualization tools and software
Ability to select appropriate visualization types for different data scenarios
Skills in customizing aesthetics and design elements of visualizations
Knowledge of conveying data-driven narratives through visualizations
Understanding of data exploration and analysis through visual representations
Statistics with Python
6 Lessons
10 hours
All Levels
What you'll learn
Understanding of key statistical concepts and terminology
Proficiency in using statistical functions and methods in Python
Knowledge of probability distributions and hypothesis testing
Skills in data sampling and estimation
Ability to analyze and interpret statistical results
Familiarity with regression analysis and predictive modeling
Understanding of statistical visualization techniques
Practical experience in applying statistical analysis to real-world datasets
Databases
4 Lessons
5 hours
All Levels
What you'll learn
Comprehensive understanding of SQL and PyMongo
Proficiency in designing and manipulating relational databases using SQL
Ability to interact with MongoDB using PyMongo
Skills in querying and managing data in both relational and NoSQL databases
Hands-on experience with real-world projects
Enhanced ability to work with databases using Python
Improved data management and querying capabilities
Trending
Python Data Expert
19 Lessons
50 hours
All Levels
What you'll learn
1. Python Arithmetic
2. Basic Data Types
3. Variables
4. Lists
5. Tuples and Strings
6. Dictionaries and Sets
7. NumPy Arrays
8. Pandas DataFrames
9. Reading and Writing Data
10. Control Flow
11. Functions
12. List Comprehensions
13. Data Exploration and Cleaning
14. Working With Text Data
15. Preparing Numeric Data
16. Dealing With Dates
17. Merging Data
18. Frequency Tables
19. Pandas
20. NumPy
Statistics with Python
6 Lessons
10 hours
All Levels
What you'll learn
Understanding of key statistical concepts and terminology
Proficiency in using statistical functions and methods in Python
Knowledge of probability distributions and hypothesis testing
Skills in data sampling and estimation
Ability to analyze and interpret statistical results
Familiarity with regression analysis and predictive modeling
Understanding of statistical visualization techniques
Practical experience in applying statistical analysis to real-world datasets
Machine Learning
8 Lessons
All Levels
What you'll learn
- Comprehensive understanding of machine learning algorithms and techniques
- Proficiency in building and training machine learning models
- Skills in evaluating and fine-tuning model performance
- Knowledge of feature engineering and data preprocessing techniques
- Ability to apply machine learning to real-world problems
- Experience with working on machine learning projects
- Understanding of model deployment and scalability considerations
- Familiarity with popular machine learning frameworks and libraries
Data Visualization
5 Lessons
20 hours
All Levels
What you'll learn
Techniques for creating compelling data visualizations
Understanding of best practices in data visualization
Proficiency in using data visualization tools and software
Ability to select appropriate visualization types for different data scenarios
Skills in customizing aesthetics and design elements of visualizations
Knowledge of conveying data-driven narratives through visualizations
Understanding of data exploration and analysis through visual representations
Databases
4 Lessons
5 hours
All Levels
What you'll learn
Comprehensive understanding of SQL and PyMongo
Proficiency in designing and manipulating relational databases using SQL
Ability to interact with MongoDB using PyMongo
Skills in querying and managing data in both relational and NoSQL databases
Hands-on experience with real-world projects
Enhanced ability to work with databases using Python
Improved data management and querying capabilities
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What you'll learn
Comprehensive understanding of SQL and PyMongo
Proficiency in designing and manipulating relational databases using SQL
Ability to interact with MongoDB using PyMongo
Skills in querying and managing data in both relational and NoSQL databases
Hands-on experience with real-world projects
Enhanced ability to work with databases using Python
Improved data management and querying capabilities
Statistics with Python
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Statistics with Python
6 Lessons
10 hours
All Levels
What you'll learn
Understanding of key statistical concepts and terminology
Proficiency in using statistical functions and methods in Python
Knowledge of probability distributions and hypothesis testing
Skills in data sampling and estimation
Ability to analyze and interpret statistical results
Familiarity with regression analysis and predictive modeling
Understanding of statistical visualization techniques
Practical experience in applying statistical analysis to real-world datasets
Data Visualization
5 Lessons
20 hours
All Levels
This course will teach students comprehensive data visualization skills using …
Free
Data Visualization
5 Lessons
20 hours
All Levels
What you'll learn
Techniques for creating compelling data visualizations
Understanding of best practices in data visualization
Proficiency in using data visualization tools and software
Ability to select appropriate visualization types for different data scenarios
Skills in customizing aesthetics and design elements of visualizations
Knowledge of conveying data-driven narratives through visualizations
Understanding of data exploration and analysis through visual representations
Python Data Expert
19 Lessons
50 hours
All Levels
This course will provide an overview of Python data types, …
Free
Python Data Expert
19 Lessons
50 hours
All Levels
What you'll learn
1. Python Arithmetic
2. Basic Data Types
3. Variables
4. Lists
5. Tuples and Strings
6. Dictionaries and Sets
7. NumPy Arrays
8. Pandas DataFrames
9. Reading and Writing Data
10. Control Flow
11. Functions
12. List Comprehensions
13. Data Exploration and Cleaning
14. Working With Text Data
15. Preparing Numeric Data
16. Dealing With Dates
17. Merging Data
18. Frequency Tables
19. Pandas
20. NumPy
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Python Data Expert
19 Lessons
50 hours
All Levels
This course will provide an overview of Python data types, …
Free
What you'll learn
1. Python Arithmetic
2. Basic Data Types
3. Variables
4. Lists
5. Tuples and Strings
6. Dictionaries and Sets
7. NumPy Arrays
8. Pandas DataFrames
9. Reading and Writing Data
10. Control Flow
11. Functions
12. List Comprehensions
13. Data Exploration and Cleaning
14. Working With Text Data
15. Preparing Numeric Data
16. Dealing With Dates
17. Merging Data
18. Frequency Tables
19. Pandas
20. NumPy
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