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DS GUEST LEC ASSIGN 7

Total questions: 17

Worksheet time: 6mins

Name
Class
Date
1.

What foundational skills were built during the Computer Engineering phase of the journey?

a)

Machine learning and statistical analysis

b)

Algorithms, systems design, and software development

c)

Scalable bot detection systems

d)

Fraud detection systems and APIs

2.

What expertise was deepened during the Master's Degree phase?

a)

Distributed CDN infrastructure

b)

Machine learning, statistical analysis, and advanced data engineering techniques

c)

Fraud detection systems and APIs

d)

Anomaly detection experience

3.

What was the strategic focus during the Job Hunt & Transition phase?

a)

Pivoting from fintech to cybersecurity and leveraging anomaly detection experience

b)

Building real-time monitoring dashboards

c)

Developing analytics pipelines

d)

Protecting high-traffic websites from automated attacks

4.

What is the current focus at Akamai Technologies?

a)

Building scalable bot detection systems across distributed CDN infrastructure

b)

Developing analytics pipelines and APIs

c)

Deepening expertise in machine learning

d)

Strategically pivoting to cybersecurity

5.

Which of the following is an example of anomaly detection in financial fraud?

a)

Monitoring patient vitals for abnormal readings.

b)

Identifying fraudulent transactions and unusual account behavior in banking systems.

c)

Detecting malicious bots in real-time network traffic.

d)

Predicting equipment failures through sensor data analysis.

6.

What is the main goal of anomaly detection in bot detection systems?

a)

To deploy detection logic across globally distributed edge servers.

b)

To build workflows that flag malicious activity in real-time and reduce manual investigation time by automating pattern validation.

c)

To query request metadata and TLS fingerprints to identify suspicious patterns.

d)

To develop heuristics and ML models for scoring bot likelihood.

7.

What is the purpose of scalable deployment in bot detection systems?

a)

To ensure consistent and low-latency protection across globally distributed edge servers.

b)

To develop heuristics and ML models for scoring bot likelihood.

c)

To query request metadata and TLS fingerprints to identify suspicious patterns.

d)

To build workflows that flag malicious activity in real-time.

8.

Which of the following technologies is described as a versatile language used for data manipulation and API development, with tools like pandas, NumPy, and Flask?

a)

Kubernetes & Docker

b)

Apache Kafka

c)

Python Ecosystem

d)

Cloud Platforms

9.

Why is cloud-native thinking considered essential according to the learning material?

a)

It is crucial for real-time data streaming.

b)

It is non-negotiable for building scalable systems.

c)

It powers distributed systems at scale.

d)

It is used for data manipulation and API development.

10.

According to the strategic approach, why is networking strategically important in job hunting?

a)

It helps in contributing to open source projects

b)

It provides opportunities through connections rather than job boards

c)

It emphasizes scalability and real-time systems

d)

It helps in practicing behavioral answers

11.

Which of the following frameworks is commonly used for building web applications in Python, known for its simplicity and flexibility?

a)

Django

b)

Flask

c)

Pyramid

d)

FastAPI

12.

What is a key benefit of using cloud-native architectures in software development?

a)

Limited deployment options

b)

Increased reliance on on-premises servers

c)

Enhanced scalability and resilience

d)

Reduced need for automated testing

13.

What is the primary function of a data pipeline in data engineering?

a)

To visualize data in real-time dashboards

b)

To store data in a relational database

c)

To perform manual data entry tasks

d)

To automate the movement and transformation of data

14.

What role does data validation play in data engineering?

a)

To ensure data integrity and accuracy

b)

To visualize data trends

c)

To store data securely

d)

To automate data entry processes

15.

Which technique is essential for improving the accuracy of anomaly detection systems?

a)

Conducting manual data audits

b)

Utilizing ensemble learning methods

c)

Developing static rule-based systems

d)

Implementing real-time data streaming

16.

We would like to know your views on the value addition to you from this session.

Please rate on a scale of 4-1 [4: Excellent, 3: Good, 2: Satisfactory, 1: Not quite satisfactory]

a)

4

b)

3

c)

2

d)

1

17.

Give two Buzz words that you understood from today's session

2 lines