TA Session 18 July: The best ROE Survival Strategies, Tricks and Tips: Part 1#

Duration: 2h 12m

Here’s an FAQ based on the provided transcript:

Tools in Data Science (TDS) Live Tutorial FAQ#

Q1: What is the agenda for this session?

A1: This session will delve deeper into some of the key topics Amit outlined in the last session, focusing on essential skills you’ll need for ROE. I won’t cover every single detail, but I’ll provide enough depth to help you succeed.

Q2: How will the ROE be delivered this time?

A2: We’ve learned from previous ROEs, and our goal is to make the process as painless as possible for you. This means mitigating known issues. The ROE won’t be a full reflection of past ROEs.

Q3: How will I receive the ROE dataset and password?

A3: You will receive the entire dataset in a password-protected zip file ahead of time. This is to prevent issues some students faced last time with downloading or accessing the portal. The password will be released on ROE day, exactly at (or very close to) 8 PM Indian Standard Time.

Q4: Where and how will I receive the ROE password?

A4: The password will definitely be available on the ROE portal itself. We also plan to post it on Discourse, and we might send a system-wide email containing it. We’ll distribute it as widely as possible to ensure you get it.

Q5: Will the zip file be sent on the same day as the ROE?

A5: No, the zip file will be sent at least a day before the ROE. This allows you to download it and sort out any potential issues beforehand.

Q6: What should I do with the zip file once I receive it?

A6: The zip file will contain many other files, which are your data sets for the ROE. On ROE day, at 8 PM IST, you will receive the password to extract these files. Tip: Create a dedicated folder on your system just for ROE. Put the zip file there and extract its contents into that same folder. This keeps everything organized.

Q7: How can I extract the zip file, especially if it’s password-protected?

A7: You’ll need appropriate software to extract zip files. Windows 11 generally handles them without issues. Recommendation: I strongly suggest using 7-Zip. It’s free, open-source, easy to use, and can handle password-protected archives. Tip: Practice extracting a sample password-protected zip file before ROE day so you’re comfortable with the process.

Q8: What software should I use for zip extraction on macOS or Linux?

A8:

macOS: I recommend using a package manager like Homebrew and installing p7zip.
Linux: gunzip is a common and straightforward tool. General Advice: Regardless of your platform, make sure you’re familiar with how to extract zip files. This is a basic skill expected at this stage of your diploma.

Q9: Is it true that ROE has too many questions and not enough time, and how should I approach this?

A9: Yes, absolutely. This is intentionally designed to challenge you, as outlined by Anand himself. My perspective is, if someone can complete everything, they’ve demonstrated exceptional skill and deserve the highest recognition. My job is to give you the tools and knowledge so you feel like you could have done it with enough time.

Q10: What are the key skills and steps I should focus on for ROE?

A10: There are three crucial skills you need to master:

Data Extraction: Be proficient in scraping data from various sources (HTML, XML, PDFs, APIs, databases, Parquet files, etc.). Have ready-made code snippets or functions that you can plug and play with minimal tweaking. Speed is critical here. Many students struggle and don’t even score marks because they can’t get past this first step.
Data Parsing/Manipulation: Once you’ve extracted the data, you need to be able to filter, transform, and manipulate it efficiently. The datasets will be too large for manual processing. Store the data in a usable format (like a Pandas DataFrame) and be comfortable with operations like dropping null values, selecting/removing columns, or converting data types.
Logical Question Breakdown: ROE questions can be complex and multi-part. Learn to logically break down a question into smaller, manageable steps. This helps you identify what information you need and in what sequence, guiding you towards the precise answer.

Q11: Will the ROE interface be similar to an OPP, or more like a standard assignment?

A11: I’m not entirely sure about the exact interface, as there have been recent changes to the portal. I’ll have to get back to you after consulting the backend team. There will be no mock ROE beforehand, so familiarity with your tools is crucial.

Q12: Will ROE answers be in an MCQ (Multiple Choice Question) format?

A12: Yes, this time, ROE answers will be in an MCQ format. This decision was made to help students and mitigate potential backend issues. However, don’t expect easy guessing. The options will be very close, requiring you to actually solve the problem to get the correct answer.

Q13: Are AI tools like ChatGPT allowed and helpful for ROE?

A13: Yes, absolutely. The professor encourages you to use ChatGPT, AI tools, and any other resources to help you quickly get to work. These tools can be very helpful for getting quick answers when you’re a bit stuck.

Q14: Should I guess if I don’t know the answer to an MCQ question?

A14: Yes! There is no negative marking for incorrect answers. If you’re unsure, definitely guess rather than leaving a question blank. You might get some marks by pure chance. Submit your answers even if incomplete.

Q15: What kind of data formats or files should I be ready to scrape and process?

A15: You should be prepared to handle various formats, including HTML files, XML files, PDF files, data from APIs, and even database or Parquet files. Make sure you have ready-made Python functions or code snippets to deal with these.

Q16: How should I structure my code snippets and notes for quick access during ROE?

A16: Create a dedicated folder for ROE on your local system. In this folder, collect all your code snippets and functions from previous weeks (especially Week 2 to Week 5 Jupyter notebooks). Don’t just copy-paste entire cells; take only the useful parts, add comments, and organize them into clean functions. Recommendation: Use Jupyter Notebook or VS Code. While Colab is allowed, working locally might be faster and prevent potential connectivity issues.

Q17: Can you suggest specific Python libraries for data extraction and parsing?

A17:

For HTML/XML parsing: BeautifulSoup (or bs4). The official documentation is an excellent resource.
For general data manipulation/filtering: Pandas.
For making web requests (for APIs): requests library.

Q18: What VS Code extensions do you recommend for ROE preparation?

A18:

Codium: A free, AI-powered autocompletion extension that provides highly relevant code suggestions and explanations. It’s comparable to GitHub Copilot. (Make sure to install the correct one: codium with spelling c-o-d-e-i-u-m).
Jupyter: Essential for running Jupyter notebooks directly within VS Code, allowing for interactive coding.
Pylance/Python: Basic but crucial extensions for Python language support, linting, and debugging.
SQL Tools/SQLite Viewer: Useful for visualizing and interacting with database files directly within VS Code, which might be helpful if you encounter database datasets.
Pylance/Python: These are basic extensions for Python language support, linting, and debugging.

Tip: Ensure you install and configure these extensions before ROE day. Practice using them, especially with password-protected files.

Q19: How many questions or datasets will there be in ROE, and how long will it last?

A19: I cannot disclose the exact number of questions, datasets, or the precise duration of the ROE. This is part of the challenge. However, it is designed to be more extensive than most people can handle within the given timeframe, unless you have exceptional experience. Tip: Focus on mastering the core skills rather than worrying about the exact specifics of the test structure.

Q20: Will this session be recorded and available later?

A20: Yes, this session is being recorded and will be available later. It will likely be uploaded to YouTube sometime tomorrow.

Q21: Will I need to use SQL in ROE, and how can I prepare for it?

A21: It’s very likely you’ll encounter scenarios requiring SQL, especially if working with databases. You should know basic SQL commands (like SELECT, WHERE). You won’t need complex joins (you can handle simple joins within Pandas after extracting). Tip: You can use Pandas functions to query dataframes with SQL-like syntax. Use ChatGPT to ask for SQL commands to query specific information. I will demonstrate how to find table names using SQL next session.

Q22: How can I access and work with database files (like SQLite) in VS Code?

A22: You can use the SQL Tools or SQLite Viewer extension in VS Code. This allows you to directly view and query the database tables without leaving your IDE. It’s very useful for understanding the database structure and filtering data.

Q23: How should I handle converting links (HTML/PDF) into local files for processing?

A23: If you are given links to data, you can use Python’s requests library to download the content and save it as a local file (e.g., HTML, PDF). Once saved locally, you can then process it using your preferred tools. This approach can be situation-dependent but is often the most effective.

Q24: Can I use the code snippets from the pre-recorded lecture notebooks?

A24: Yes, you can use those. However, I advise against simply copying and pasting entire cells. Instead, extract only the useful parts that you understand, add your own comments, and integrate them into your organized code snippets. Many pre-recorded lecture notebooks contain extraneous code, and not all of it is directly useful for ROE.

Q25: How should I approach using LLMs like ChatGPT during ROE, especially concerning token limits?

A25:

Token Use: Be mindful that your API key for LLMs (like OpenAI) has an allowance. You’ll be given a token quota for ROE. Make sure you understand how tokens are consumed.
Training LLM: Use a single, continuous chat window with your LLM. Don’t start a new chat for every question. As you interact, the LLM builds context and “trains” itself on your conversation, making its responses more accurate and quicker for ROE-related questions.
Question Specificity: In ROE, questions involving LLMs will be very specific to avoid ambiguity. For example, they might specify which tokenizer to use if token counting is involved.

Q26: What about parsing specific classes or attributes within HTML/XML tags?

A26: Beautiful Soup allows you to search for tags based on their attributes (like class or id). You can specify the tag name and then provide a dictionary of attributes. For example, soup.find_all('p', {'class': 'strikeout'}) would find all <p> tags with the class “strikeout.” Tip: Practice this to confidently target specific elements based on their attributes.

Q27: What are the risks of using online tools like Google Colab for ROE?

A27: While Colab is allowed, working locally (with VS Code/Jupyter Notebook) is generally recommended. Risk: If you experience an internet connectivity issue while using Colab, you could lose all your work. We have had students in the past who lost significant progress due to Colab issues. Recommendation: Work offline on your local computer to avoid such risks. If you do use Colab, frequently save your work and download copies.

Q28: How should I handle iterating through multiple files in a directory?

A28: This is a crucial skill for ROE. You can use Python’s os library (os.listdir) to get a list of all files in a directory. Then, you can iterate through this list using a for loop, opening and processing each file one by one. Tip: Practice this with various file types (HTML, TXT, etc.) to become comfortable with the loop structure and file handling.

Q29: How can I process and filter data once it’s in a Pandas DataFrame?

A29: Pandas DataFrames are excellent for this. You can perform various operations like:

Filtering: df[df['column'] == 'value'] or df[~df['column'].isna()] (to find non-nulls).
Chaining Conditions: Use & (and) or | (or) operators to combine multiple filtering conditions within parentheses (e.g., df[(df['col1'] > 10) & (df['col2'] == 'A')]).
Transformations: Convert data types, apply functions to columns, fill missing values, etc. Tip: Practice chaining multiple filters. Be careful with parentheses to ensure correct logical grouping.

Q30: Where can I find good practice datasets for ROE?

A30: I recommend visiting relational.data.org. They offer a variety of datasets that you can use to practice your extraction, parsing, and data manipulation skills. Tip: Start with simple datasets to get comfortable with the tools, then gradually move to more complex ones.

Q31: Will ROE require me to use Excel, or will I need specific tools for PDF processing?

A31: ROE will not test your Excel skills, as not everyone has access to Excel. For PDFs, there are three main approaches:

Tabula: A Python library specifically designed for extracting tabular data from PDFs.
I love PDF: An online service (ilovepdf.com) that can convert PDFs to various formats, including Excel or CSV.
Direct Import to Excel: Some PDFs might be directly importable into Excel (though this won’t be required for ROE).

Recommendation for PDFs: Tabula is great for clean PDFs. I love PDF is a good online option if conversion is needed. Tip: Practice using Tabula with a simple PDF file to extract tabular data.

Q32: What’s the biggest advice you can give for ROE preparation?

A32: Speed is life in ROE. Master the three key skills:

Iterate through files/data sources: Quickly access and read data.
Extract information: Efficiently pull out relevant details using tools like Beautiful Soup or Pandas.
Process/Filter data: Rapidly manipulate and narrow down data to find answers.

Tip: Practice with simple datasets. Don’t try to tackle overly complex examples initially, as that will distract from mastering the tools themselves. Once you’re fast and comfortable with the tools, then tackle complexity.

Q33: Can you tell me more about the VS Code extensions you recommended?

A33:

Codium: (Spelled C-O-D-E-I-U-M). This is an AI-powered code completion and suggestion tool. It provides highly relevant code snippets and explanations as you type, significantly speeding up coding.
Jupyter: This extension allows you to open and run .ipynb (Jupyter Notebook) files directly within VS Code, offering an interactive coding experience.
Pylance/Python: These provide essential Python language support, including linting, debugging, and auto-completion.
SQL Tools / SQLite Viewer: These extensions enable you to view and interact with SQL databases (like SQLite files) directly within VS Code. You can browse tables, run queries, and inspect data.
Pylance/Python: These are the fundamental extensions for Python language support, linting, and debugging within VS Code.

Q34: How should I prepare my code snippets and notes for ROE?

A34:

Keep Snippets Organized: Create a dedicated notebook or markdown file (e.g., snippets.md) where you store small, self-contained pieces of code for common tasks (e.g., reading different file types, common Pandas operations, Beautiful Soup commands).
Use Markdowns for Structure: Within your snippet file, use markdown headers (e.g., ## Extraction - HTML, ### Pandas - Filtering) to categorize your snippets.
Add Keywords: Add keywords to your markdown notes (e.g., ) to make them easily searchable.
Practice Locating: Practice finding your snippets quickly using your IDE’s search function.
“Cheat Sheet” Analogy: Think of your snippet file as a well-organized cheat sheet. Practice using it during your prep. The goal is to make it second nature to find what you need quickly.

Q35: Is it possible to use SQL directly with Pandas DataFrames for filtering?

A35: Yes, it is possible. You can use libraries that allow you to write SQL-like queries directly on Pandas DataFrames. This can be a powerful way to filter and manipulate your data if you’re comfortable with SQL. Note: I won’t go into deep detail on this in the session, as it’s not a core expectation for ROE, but it’s a useful skill to know.

Q36: Will the ROE involve tasks that require working with multiple files simultaneously?

A36: Yes, definitely. You should expect to work with multiple files. The ROE might involve:

Many files: You could have 10, 50, or even more files in a directory.
Different file types: These files might contain various types of information (e.g., one HTML, another XML, a third PDF).
Combining information: You might need to extract information from several files and combine it to answer a single question.

Tip: Practice iterating through a list of files in a directory, opening each one, extracting data, and then consolidating that data into a single Pandas DataFrame.

*(End of FAQ)*Here’s an FAQ based on the provided transcript:

Tools in Data Science (TDS) Live Tutorial FAQ#

Q1: What is the agenda for this session?

Q2: How will I receive the ROE dataset and password?

A2: You will receive the entire dataset in a password-protected zip file ahead of time. This is to prevent issues some students faced last time with downloading or accessing the portal. The password will be released on ROE day, exactly at (or very close to) 8 PM Indian Standard Time.

Q3: Where and how will I receive the ROE password?

A3: The password will definitely be available on the ROE portal itself. We also plan to post it on Discourse, and we might send a system-wide email containing it. We’ll distribute it as widely as possible to ensure you get it.

Q4: Will the zip file be sent on the same day as the ROE?

A4: No, the zip file will be sent at least a day before the ROE. This allows you to download it and sort out any potential issues beforehand. We might also include a checksum to verify the file’s integrity, but this is not yet finalized.

Q5: What should I do with the zip file once I receive it?

A5: The zip file will contain many other files, which are your data sets for the ROE. On ROE day, at 8 PM IST, you will receive the password to extract these files. Tip: Create a dedicated folder on your system just for ROE. Put the zip file there and extract its contents into that same folder. This keeps everything organized.

Q6: How can I extract the zip file, especially if it’s password-protected?

A6: You’ll need appropriate software to extract zip files. Windows 11 generally handles them without issues. Recommendation: I strongly recommend using 7-Zip. It’s free, open-source, easy to use, and can handle password-protected archives. Tip: Practice extracting a sample password-protected zip file before ROE day so you’re comfortable with the process.

Q7: What software should I use for zip extraction on macOS or Linux?

A7:

macOS: I recommend using a package manager like Homebrew and installing p7zip.
Linux: gunzip is a common and straightforward tool. General Advice: Regardless of your platform, make sure you’re familiar with how to extract zip files. This is a basic skill expected at this stage of your diploma.

Q8: Is it true that ROE has too many questions and not enough time, and how should I approach this?

A8: Yes, absolutely. This is intentionally designed to challenge you, as outlined by Anand himself. My perspective is, if someone can complete everything, they’ve demonstrated exceptional skill and deserve the highest recognition. My job is to give you the tools and knowledge so you feel like you could have done it with enough time.

Q9: What are the key skills and steps I should focus on for ROE?

A9: There are three crucial skills you need to master:

Data Extraction: Be proficient in scraping data from various sources (HTML, XML, PDFs, APIs, databases, Parquet files, etc.). Have ready-made code snippets or functions that you can plug and play with minimal tweaking. Speed is critical here. Many students struggle and don’t even score marks because they can’t get past this first step.
Data Parsing/Manipulation: Once you’ve extracted the data, you need to be able to filter, transform, and manipulate it efficiently. The datasets will be too large for manual processing. Store the data in a usable format (like a Pandas DataFrame) and be comfortable with operations like dropping null values, selecting/removing columns, or converting data types.
Logical Question Breakdown: ROE questions can be complex and multi-part. Learn to logically break down a question into smaller, manageable steps. This helps you identify what information you need and in what sequence, guiding you towards the precise answer.

Q10: Will the ROE interface be similar to an OPP, or more like a standard assignment?

A10: I’m not entirely sure about the exact interface, as there have been recent changes to the portal. I’ll have to get back to you after consulting the backend team. There will be no mock ROE beforehand, so familiarity with your tools is crucial.

Q11: Will ROE answers be in an MCQ (Multiple Choice Question) format?

A11: Yes, this time, ROE answers will be in an MCQ format. This decision was made to help students and mitigate potential backend issues. However, don’t expect easy guessing. The options will be very close, requiring you to actually solve the problem to get the correct answer.

Q12: Should I guess if I don’t know the answer to an MCQ question?

A12: Yes! There is no negative marking for incorrect answers. If you’re unsure, definitely guess rather than leaving a question blank. You might get some marks by pure chance. Submit your answers even if incomplete.

Q13: Are AI tools like ChatGPT allowed and helpful for ROE?

Q14: What kind of data formats or files should I be ready to scrape and process?

A14: You should be prepared to handle various formats, including HTML files, XML files, PDF files, data from APIs, and even database or Parquet files. Make sure you have ready-made Python functions or code snippets to deal with these.

Q15: How should I structure my code snippets and notes for quick access during ROE?

A15: Create a dedicated folder for ROE on your local system. In this folder, collect all your code snippets and functions from previous weeks (especially Week 2 to Week 5 Jupyter notebooks). Don’t just copy-paste entire cells; take only the useful parts, add comments, and organize them into clean functions. Recommendation: Use Jupyter Notebook or VS Code. While Colab is allowed, working locally might be faster and prevent potential connectivity issues.

Q16: Can you suggest specific Python libraries for data extraction and parsing?

A16:

For HTML/XML parsing: BeautifulSoup (or bs4). The official documentation is an excellent resource.
For general data manipulation/filtering: Pandas.
For making web requests (for APIs): requests library.

Q17: What VS Code extensions do you recommend for ROE preparation?

A17:

Codium: (Spelled C-O-D-E-I-U-M). This is an AI-powered autocompletion extension that provides highly relevant code suggestions and explanations. It’s free and highly rated.
Jupyter: Essential for running .ipynb files directly within VS Code.
Pylance/Python: Basic but crucial for Python language support.
SQL Tools/SQLite Viewer: Useful for viewing and interacting with database files.

Tip: Install and configure these extensions before ROE day. Practice using them, especially with password-protected files.

Q18: What are the risks of using online tools like Google Colab for ROE?

A18: While Colab is allowed, working locally (with VS Code/Jupyter Notebook) is generally recommended. Risk: If you experience an internet connectivity issue while using Colab, you could lose all your work. Past students have faced significant progress loss due to Colab issues. Recommendation: Work offline on your local computer to avoid such risks. If you do use Colab, frequently save your work and download copies.

Q19: How should I handle iterating through multiple files in a directory?

A19: This is a crucial skill for ROE. You can use Python’s os library (os.listdir) to get a list of all files in a directory. Then, you can iterate through this list using a for loop, opening and processing each file one by one. Tip: Practice this with various file types (HTML, TXT, etc.) to become comfortable with the loop structure and file handling.

Q20: Will I need to use SQL in ROE, and how can I prepare for it?

A20: It’s very likely you’ll encounter scenarios requiring SQL, especially if working with databases. You should know basic SQL commands (like SELECT, WHERE). You won’t need complex joins (you can handle simple joins within Pandas after extracting). Tip: You can ask ChatGPT for basic SQL commands. I will demonstrate how to find table names using SQL next session.

Q21: How can I process and filter data once it’s in a Pandas DataFrame?

A21: Pandas DataFrames are excellent for this. You can perform various operations like:

Filtering: df[df['column'] == 'value'] or df[~df['column'].isna()] (to find non-nulls).
Chaining Conditions: Use & (and) or | (or) operators to combine multiple filtering conditions within parentheses (e.g., df[(df['col1'] > 10) & (df['col2'] == 'A')]).
Transformations: Convert data types, apply functions to columns, fill missing values, etc. Tip: Practice chaining multiple filters. Be careful with parentheses to ensure correct logical grouping.

Q22: How should I prepare my code snippets and notes for ROE?

A22:

Keep Snippets Organized: Create a dedicated notebook or markdown file (e.g., snippets.md) where you store small, self-contained pieces of code for common tasks (e.g., reading different file types, common Pandas operations, Beautiful Soup commands).
Use Markdowns for Structure: Within your snippet file, use markdown headers (e.g., ## Extraction - HTML, ### Pandas - Filtering) to categorize your snippets.
Add Keywords: Add keywords to your markdown notes (e.g., ) to make them easily searchable.
Practice Locating: Practice finding your snippets quickly using your IDE’s search function.
“Cheat Sheet” Analogy: Think of your snippet file as a well-organized cheat sheet. Practice using it during your prep. The goal is to make it second nature to find what you need quickly.

Q23: Will ROE involve LLMs (Large Language Models) or require using their APIs?

A23: Yes, it’s almost guaranteed you’ll encounter an ROE question that involves LLMs and requires using their API. The token quota for ROE will be refilled on ROE day, which is a strong indication. Tip: Be comfortable with LLM API usage. The sessions have covered this, so revisit them. Ensure you understand LLM costing and data extraction from LLM responses.

Q24: What about embedding content or parsing specific classes/attributes within HTML/XML tags?

A24: Beautiful Soup allows you to search for tags based on their attributes (like class or id). You can specify the tag name and then provide a dictionary of attributes. For example, soup.find_all('p', {'class': 'strikeout'}) would find all <p> tags with the class “strikeout.” Tip: Practice this to confidently target specific elements based on their attributes.

Q25: What other types of files or databases should I be familiar with for ROE?

A25: Besides HTML and XML, you might encounter PDF files or Parquet files.

PDFs: You can use libraries like Tabula (for tabular data) or online services like ilovepdf.com to extract information or convert PDFs to other formats.
Parquet: Ensure you can load and read Parquet files into a Pandas DataFrame.

Q26: Will there be multiple tables in the database, and how can I find their names?

A26: Yes, there will likely be multiple tables in a database. I’ll provide the SQL command to list all tables in a database in the next session. You can also ask ChatGPT for such basic SQL commands.

Q27: How can I join tables from a database using Pandas?

A27: You can extract each table into separate Pandas DataFrames. Then, use Pandas’ concat or merge functions (similar to SQL JOIN) to combine them based on a common column (key). This will create a third DataFrame with the joined information.

Q28: What is the biggest advice you can give for ROE preparation?

A28: Speed is life in ROE. Master the three key skills:

Iterate through files/data sources: Quickly access and read data.
Extract information: Efficiently pull out relevant details using tools like Beautiful Soup or Pandas.
Process/Filter data: Rapidly manipulate and narrow down data to find answers.

Q29: Are the weekly live session notebooks available for review?

A29: We generally do not share the live session notebooks. The idea is for you to actively participate and practice building them yourself. However, you can access the pre-recorded lecture notebooks.

Q30: How should I use the pre-recorded lecture notebooks for preparation?

A30: You can certainly use the code from the pre-recorded lecture notebooks. However, instead of just copy-pasting everything, I recommend:

Understand the Code: Don’t copy-paste without understanding what each part does.
Extract Useful Snippets: Most lecture notebooks have a lot of explanatory code. Take only the concise, reusable parts that perform specific tasks.
Organize Your Snippets: Integrate these useful snippets into your own well-organized notebook or code file, with comments and keywords.

Q31: What are the general recommended extensions for VS Code?

A31:

Codium: (Codeium) for AI-powered code completion.
Jupyter: For running .ipynb files.
Pylance/Python: For Python language support.
SQL Tools/SQLite Viewer: For interacting with databases.
Pylance/Python: For basic Python language features.

Q32: Can I use Anaconda Jupyter Lab or other local IDEs?

A32: Yes, absolutely. Any local IDE that helps you work effectively (like Anaconda Jupyter Lab or even the standalone Jupyter Notebook software) is perfectly acceptable. The main advantage is working offline, which is faster and avoids potential data loss due to connectivity issues.

Q33: Will there be any “optional” questions in the ROE?

A33: No, typically there are no “optional” questions in ROE. You are generally expected to attempt all questions.