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Microsoft Azure Data Scientist DP-100 [2023/2024]
Microsoft Azure Data Scientist DP-100 [2023/2024]. Data Scientist.
Course Description
The Data Scientist Practice Test is designed to assess and reinforce the skills and knowledge acquired throughout the Data Scientist training program. This comprehensive test encompasses a range of topics essential to the field of data science, providing participants with a simulated real-world experience.
Key Learning Objectives:
- Data Exploration and Cleaning: Evaluate your ability to understand and clean diverse datasets, addressing missing values, outliers, and anomalies.
- Statistical Analysis: Demonstrate your proficiency in applying statistical methods to extract meaningful insights from data, including hypothesis testing and regression analysis.
- Machine Learning Algorithms: Showcase your understanding of various machine learning algorithms, their applications, and the ability to select the most suitable algorithm for a given problem.
- Feature Engineering: Assess your skills in feature engineering to enhance model performance and interpretability.
- Model Evaluation and Optimization: Evaluate your capability to assess model performance, tune hyperparameters, and optimize machine learning models.
- Data Visualization: Demonstrate your skill in creating clear and insightful data visualizations to communicate findings effectively.
- Big Data Technologies: Test your knowledge of big data technologies and distributed computing frameworks for handling large-scale datasets.
- Ethical Considerations: Explore ethical implications related to data science, including privacy, bias, and responsible AI.
Who Should Take This Course:
This practice test is suitable for individuals who have completed foundational training in data science and want to assess their readiness for real-world challenges. It is also valuable for professionals preparing for data scientist certification exams.
Prerequisites:
Completion of a foundational data science training program or equivalent knowledge and experience in statistics, programming (e.g., Python or R), and machine learning concepts.
Outcome:
Successful completion of the Data Scientist Practice Test indicates a strong foundation in data science concepts and readiness for real-world applications. Participants will receive detailed feedback on their performance to guide further learning and improvement.
