Study Blog
# MCQ Number 3
Many of the mistakes I made regarding the MCQ were mistakes made by lack of focus and a late night session. I understand that my problem with these questions was lack of focus and improper reading of the question, and to improve my MC score, I will be re-doing practice questions to familiarize myself with the format of the exam.
# Study Plan
**Week of April 21st**: Finish up to Unit 8 of Khan Academy AP CSP Course to familiarize and practice topics in areas of weakness
**Weekend of April 26th**: Re-take MCQ 1 to improve score
**Week of April 28th**: Review any incorrect questions from MCQ 1, understand the incorrect topics, finish Units 9-10 of AP CSP in Khan Academy. Final revision of CPT Project.
**Weekend of May 3rd**: Retake MCQ 2 to improve score.
**Week of May 5th-May 12th**: Review incorrect questions from MCQ 2 and understand the incorrect topics. Begin preparing for the FRQ by reviewing code and explaining code segments and their functionality, line by line.
**May 12th to Exam Day**: Last minute topics that need review + Final MCQ Check ### Credentials: | Type | Credential / Project Name | Description | |-------------|-------------------------------------|-------------| | **Certificate** | Tools Basics | Proficiency with GitHub, terminal usage, and structured version control through Issues, PRs, and commits. | | **Certificate** | Full Stack Development | Connected frontend interfaces with backend Flask APIs using async fetch, managing CRUD operations with SQLite. | | **Certificate** | Data Analysis with Python | Applied Pandas, NumPy, and statistical models to predict heart disease risk using real health datasets. | | **Certificate** | API Development | Designed and tested APIs for book journal, trivia quiz, and health risk prediction using Postman. | | **NFT** | Biotech Trivia Generator | Designed a dynamic quiz engine that pulls bias-free questions from Gemini via a custom API. Demonstrated prompt engineering and data parsing. | | **NFT** | Heart Disease Risk Model | Created a hybrid ML + equation-based predictor combining a trained model with Framingham coefficients to calculate 10-year cardiovascular risk. | | **NFT** | Personalized Book Journal | Developed a personal book tracking system with custom API routes, live updates, and aesthetic card-style UI. |
Many of the mistakes I made regarding the MCQ were mistakes made by lack of focus and a late night session. I understand that my problem with these questions was lack of focus and improper reading of the question, and to improve my MC score, I will be re-doing practice questions to familiarize myself with the format of the exam.
# Study Plan
**Week of April 21st**: Finish up to Unit 8 of Khan Academy AP CSP Course to familiarize and practice topics in areas of weakness
**Weekend of April 26th**: Re-take MCQ 1 to improve score
**Week of April 28th**: Review any incorrect questions from MCQ 1, understand the incorrect topics, finish Units 9-10 of AP CSP in Khan Academy. Final revision of CPT Project.
**Weekend of May 3rd**: Retake MCQ 2 to improve score.
**Week of May 5th-May 12th**: Review incorrect questions from MCQ 2 and understand the incorrect topics. Begin preparing for the FRQ by reviewing code and explaining code segments and their functionality, line by line.
**May 12th to Exam Day**: Last minute topics that need review + Final MCQ Check ### Credentials: | Type | Credential / Project Name | Description | |-------------|-------------------------------------|-------------| | **Certificate** | Tools Basics | Proficiency with GitHub, terminal usage, and structured version control through Issues, PRs, and commits. | | **Certificate** | Full Stack Development | Connected frontend interfaces with backend Flask APIs using async fetch, managing CRUD operations with SQLite. | | **Certificate** | Data Analysis with Python | Applied Pandas, NumPy, and statistical models to predict heart disease risk using real health datasets. | | **Certificate** | API Development | Designed and tested APIs for book journal, trivia quiz, and health risk prediction using Postman. | | **NFT** | Biotech Trivia Generator | Designed a dynamic quiz engine that pulls bias-free questions from Gemini via a custom API. Demonstrated prompt engineering and data parsing. | | **NFT** | Heart Disease Risk Model | Created a hybrid ML + equation-based predictor combining a trained model with Framingham coefficients to calculate 10-year cardiovascular risk. | | **NFT** | Personalized Book Journal | Developed a personal book tracking system with custom API routes, live updates, and aesthetic card-style UI. |