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Data Science Lab
Gen AI Lab
Network+ Lab
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Data Science Lab: Customer Analytics & Predictive Modeling
Advanced Lab
Scenario: E-Commerce Customer Churn Analysis
You are a Data Scientist at GlobalShop Inc., an e-commerce company experiencing a 15% customer churn rate. The CEO has tasked you with analyzing customer behavior data to identify at-risk customers and build a predictive model. Your analysis will drive a $2M retention marketing campaign targeting the right customers at the right time.

Learning Objectives:

  • SQL Data Extraction: Write complex queries to extract and transform customer data from multiple tables
  • Exploratory Data Analysis: Identify patterns, correlations, and anomalies in customer behavior
  • Feature Engineering: Create meaningful features like RFM scores, engagement metrics, and cohort analysis
  • Statistical Analysis: Apply hypothesis testing and confidence intervals to validate findings
  • Data Visualization: Create compelling charts and dashboards to communicate insights

Dataset Configuration

Analysis Settings

ML Model Settings

Visualization Settings

PostgreSQL 15 - Customer Analytics Database

-- PostgreSQL 15.4 on Linux x86_64
-- Connected to database: customer_analytics
-- Type your SQL query below and click Execute
--
-- Available tables: customers, orders, products, sessions
-- Required query must include: SELECT, FROM customers, JOIN orders, GROUP BY, churn_risk
 
analytics=#

Pro Tips & Hints

  • RFM Analysis: Calculate Recency, Frequency, and Monetary scores to segment customers effectively
  • Cohort Analysis: Group customers by signup month to track retention over time
  • Window Functions: Use LAG() and LEAD() to compare customer behavior over time periods
  • CTEs: Use Common Table Expressions for cleaner, more readable complex queries
Lab Progress: 0/5 analysis steps completed

Data Science Lab Complete! Skills Mastered:

SQL Analytics

Complex queries, aggregations, and window functions

Customer Segmentation

RFM analysis and churn prediction modeling

Data Visualization

Creating insightful charts and dashboards

Business Intelligence

Translating data into actionable insights

Generative AI Lab: Enterprise Chatbot Development
Advanced Lab
Scenario: Building an AI-Powered Customer Support System
TechStart Inc. wants to implement an AI-powered customer support chatbot to handle 70% of routine inquiries. As the AI/ML Engineer, you must configure a Large Language Model (LLM) with appropriate prompt engineering, safety guardrails, and response optimization. The system must handle product questions, troubleshooting, and order status while maintaining brand voice and avoiding hallucinations.

Learning Objectives:

  • Prompt Engineering: Design effective system prompts, few-shot examples, and context management
  • Model Configuration: Tune temperature, top-p, and token limits for optimal response quality
  • Safety & Guardrails: Implement content filtering, PII detection, and response validation
  • RAG Integration: Connect knowledge base for accurate, grounded responses
  • Performance Optimization: Balance latency, cost, and quality trade-offs

Model Configuration

Precise (0) Creative (2)

Safety & Guardrails

Prompt Engineering Studio

System Prompt Token Count: 287
Send the first test prompt to begin the conversation.
Progress: 0/3 prompts completed

Pro Tips & Best Practices

  • Temperature: Use 0.0-0.3 for factual Q&A, 0.7-1.0 for creative tasks. Customer support typically works best at 0.3-0.5
  • Few-Shot Examples: Include 2-3 example conversations in your system prompt to establish desired response format
  • Chain-of-Thought: For complex queries, instruct the model to "think step by step" before answering
  • Grounding: Always use RAG to retrieve relevant docs before generating responses to reduce hallucinations
Lab Progress: 0/5 configuration steps completed

Gen AI Lab Complete! Skills Mastered:

Prompt Engineering

System prompts, few-shot learning, and context management

Model Configuration

Temperature tuning, token limits, and response optimization

Safety Implementation

Content filtering, PII protection, and guardrails

Production Deployment

Latency optimization and cost management

Network+ Lab: Multi-Site Enterprise Network Implementation
Advanced Lab
Scenario: Healthcare Network Infrastructure Deployment
MedTech Hospital is opening a new 500-bed facility and needs a HIPAA-compliant network infrastructure. As the Senior Network Engineer, you must design and configure a segmented network with multiple VLANs for patient data, medical devices, administrative systems, and guest access. The network must support high-availability, QoS for VoIP and telemedicine, and strict access controls between departments.

Learning Objectives:

  • VLAN Configuration: Implement network segmentation for security isolation between departments
  • Inter-VLAN Routing: Configure Layer 3 switching for controlled traffic flow between segments
  • Spanning Tree Protocol: Implement STP/RSTP for loop prevention and redundancy
  • QoS Implementation: Prioritize critical traffic like VoIP and medical telemetry
  • Network Security: Apply ACLs, port security, and 802.1X authentication

Components

Drag to drop zones
IDS/IPS Sensor
Load Balancer
Wireless Ctrl
VPN Concentrator

Healthcare Network Topology - Drag components to complete the diagram

Core Layer
Distribution Layer
Access Layer
Servers/Services
WAN / Internet Zone
Internet / WAN
Edge / DMZ Zone
Security Appliance
CORE-RTR-01
10.0.0.1
NGFW-01
10.0.0.254
Network Service
Distribution Layer
DIST-SW-01
L3 Switch
10.0.1.1
Wireless Device
DIST-SW-02
L3 Switch
10.0.1.2
Access Layer
ACC-SW-01
VLAN 10
ACC-SW-02
VLAN 20
ACC-SW-03
VLAN 30
WLC-01
VLAN 40
Endpoints
Workstation
Med Device
Printer
Mobile
DB Server
VLAN 10 Patient Data 172.16.10.0/24
VLAN 20 Medical Devices 172.16.20.0/24
VLAN 30 Admin/Staff 172.16.30.0/24
VLAN 40 Guest WiFi 172.16.40.0/24

VLAN Configuration

Switch Port Configuration

Cisco IOS CLI - DIST-SW-01

! Cisco IOS CLI - Enter your configuration commands below
! Paste the required commands from the instructions panel
!
! Required commands to configure VLAN 10 (Patient Data):
! configure terminal
! vlan 10
! name PATIENT_DATA
! exit
! interface vlan 10
! ip address 172.16.10.1 255.255.255.0
! no shutdown
! end
!
DIST-SW-01#

Pro Tips & Hints

  • VLAN 1: Never use VLAN 1 for user traffic - it's the default and poses security risks
  • Native VLAN: Use a dedicated management VLAN (like 99) as native to prevent VLAN hopping attacks
  • STP: Enable BPDU Guard on access ports to prevent rogue switches from disrupting the network
  • QoS: Mark voice traffic with DSCP EF (46) for priority queuing across the network
Lab Progress: 0/6 devices configured

Network+ Lab Complete! Skills Mastered:

VLAN Implementation

Network segmentation and isolation for security

Inter-VLAN Routing

Layer 3 switching and SVI configuration

Spanning Tree Protocol

Loop prevention and network redundancy

Network Security

Port security, BPDU Guard, and ACL implementation

Practice Questions: Multi-Certification Exam Prep
3 Questions

Test your knowledge across three major certification domains: Security+, CISSP, and CISM

CompTIA Security+ (SY0-701)
Domain 1.0: Attacks & Threats
A security analyst discovers that an attacker has gained access to the network by exploiting a vulnerability in a public-facing web application. The attacker then moved laterally through the network, escalated privileges, and exfiltrated sensitive data over an encrypted channel. Which of the following BEST describes this type of attack?
A. Denial of Service (DoS) attack
B. SQL injection attack
C. Advanced Persistent Threat (APT)
D. Brute force attack

Correct Answer: C. Advanced Persistent Threat (APT)

An APT is characterized by a sophisticated, multi-stage attack where threat actors gain initial access, establish persistence, move laterally, escalate privileges, and exfiltrate data over time. The use of encrypted channels for data exfiltration is a common APT technique to avoid detection.

ISC² CISSP
Domain 3: Security Architecture
An organization is implementing a zero-trust architecture. The security team needs to ensure that all access requests are verified regardless of the source. According to zero-trust principles, which of the following should be the PRIMARY basis for granting access to resources?
A. Network location and IP address
B. Continuous verification of identity, device health, and context
C. VPN connection from an approved corporate device
D. User's department and job title

Correct Answer: B. Continuous verification of identity, device health, and context

Zero-trust architecture operates on the principle of "never trust, always verify." Access decisions should be based on continuous verification of multiple factors including user identity, device posture, behavior analytics, and contextual information—not just network location or static credentials.

ISACA CISM
Domain 1: Information Security Governance
The board of directors has asked the information security manager to demonstrate the value of the security program. Which of the following metrics would BEST demonstrate alignment between security initiatives and business objectives?
A. Number of security patches applied per month
B. Reduction in security incidents affecting critical business processes
C. Total number of firewall rules implemented
D. Hours spent on security awareness training

Correct Answer: B. Reduction in security incidents affecting critical business processes

To demonstrate business value, security metrics should be tied to business outcomes rather than technical activities. Showing how security initiatives have reduced incidents impacting critical business processes directly links security efforts to protecting business value and supports strategic decision-making.

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Network+ Lab Instructions

Lab Objective

Design and configure a HIPAA-compliant healthcare network with proper segmentation, security controls, and high-availability features. You will deploy security appliances by dragging them from the palette, configure VLANs, and set up switch port security.

1
Pending
Deploy Security Appliances
Drag the IDS/IPS Sensor from the component palette to the left drop zone. Then drag the Load Balancer to the right drop zone. These appliances will protect the network perimeter and distribute traffic.
Pro Tip

IDS/IPS should be placed between the firewall and distribution layer to inspect all traffic entering the internal network segments.

2
Pending
Configure VLAN Segmentation
Select VLAN 10 - Patient Data from the dropdown and enter the following settings:
  • Subnet: 172.16.10.0/24
  • Gateway: 172.16.10.1
  • DHCP Range: 172.16.10.100 - 172.16.10.200
Hint

For HIPAA compliance, patient data must be isolated on its own VLAN with restricted inter-VLAN routing rules.

3
Pending
Configure Trunk Ports
In the Switch Port Configuration panel:
  • Set Port Mode to Trunk
  • Set Native VLAN to 99
  • Enter Allowed VLANs: 10,20,30,40,99
Warning

Never use VLAN 1 as the native VLAN. This is a common security misconfiguration that enables VLAN hopping attacks.

4
Pending
Enable Port Security Features
Enable the following security features on access ports:
  • PortFast - For faster convergence on edge ports
  • BPDU Guard - Prevents rogue switch connections
Pro Tip

Enable Root Guard on distribution switch ports to prevent unauthorized STP topology changes from the access layer.

5
Pending
Apply CLI Configuration
Copy and paste these EXACT commands into the CLI textarea: 
configure terminal
vlan 10
name PATIENT_DATA
exit
interface vlan 10
ip address 172.16.10.1 255.255.255.0
no shutdown
end

Click "Apply Config" to execute, then click "Submit Network Configuration"

Critical

Commands must be typed EXACTLY as shown. The system validates each command. At least 6 of 8 commands must match.

Lab Progress

0/5

Data Science Lab Instructions

Lab Objective

Analyze customer data to identify churn patterns and build a predictive model. You will write SQL queries, perform data analysis, and create visualizations to support business decisions.

1
Pending
Configure Dataset Settings
Configure these EXACT values in the Dataset Configuration panel:
  • 1. Select Dataset: E-Commerce Transactions (500K rows)
  • 2. Date Range: Start: 2024-01-01 | End: 2024-12-31
  • 3. Sample Size: 50000
  • 4. Aggregation Level: Monthly
  • 5. Customer Segment: Churned Customers (90+ days inactive)
Pro Tip

Monthly aggregation helps identify seasonal churn patterns while keeping the dataset manageable.

2
Pending
Configure Analysis Settings
Set these EXACT values in the Analysis Settings panel:
  • 6. Churn Threshold (days): 90
  • 7. RFM Recency Weight: 0.4
  • 8. RFM Frequency Weight: 0.3
  • 9. RFM Monetary Weight: 0.3
  • 10. Statistical Test: Chi-Square Test
Note

RFM weights must sum to 1.0 (0.4 + 0.3 + 0.3 = 1.0). Recency gets higher weight because recent inactivity is the strongest churn predictor.

3
Pending
Run SQL Query in Terminal
Copy and paste this EXACT SQL query into the SQL terminal: 
SELECT c.customer_id, c.customer_name, c.signup_date, 
       COUNT(o.order_id) as total_orders,
       SUM(o.amount) as lifetime_value,
       DATEDIFF(NOW(), MAX(o.order_date)) as days_since_order,
       CASE WHEN DATEDIFF(NOW(), MAX(o.order_date)) > 90 
            THEN 'High' ELSE 'Low' END as churn_risk
FROM customers c
LEFT JOIN orders o ON c.customer_id = o.customer_id
GROUP BY c.customer_id, c.customer_name, c.signup_date
ORDER BY churn_risk DESC, days_since_order DESC;

Click query to copy

Then click "Run Query". The query must contain at least 5 of these 7 keywords: SELECT, FROM, customers, orders, JOIN, GROUP BY, churn
Important

The terminal strictly validates your query. Invalid queries will show an error with missing keywords. Copy the query exactly as shown above.

4
Pending
Configure ML & Visualization Settings
Set these EXACT values in the ML Model Settings and Visualization panels:
  • 11. Prediction Model: Random Forest
  • 12. Train/Test Split: 80
  • 13. Confidence Level: 95%
  • 14. Cross-Validation Folds: 5
  • 15. Chart Type: Bar Chart
  • 16. Color Scheme: Viridis
  • 17. Output Format: CSV Export
  • ☑️ Show Grid Lines - Checked
  • ☑️ Show Legend - Checked
  • ☑️ Show Confidence Intervals - Checked
Pro Tip

Random Forest with 5-fold cross-validation provides robust churn predictions while avoiding overfitting.

5
Pending
Submit Analysis
Review your findings and click "Submit Analysis" to complete the lab. Your analysis should identify at-risk customers for the retention campaign.
Hint

A good analysis identifies both high-value churning customers (prioritize) and patterns that predict churn early.

Gen AI Lab Instructions

Lab Objective

Configure an enterprise chatbot with proper prompt engineering, safety guardrails, and response optimization. Your chatbot should handle customer queries accurately and professionally.

1
Pending
Select Model & Configure Parameters
Set these EXACT values in the Model Configuration panel:
  • Model: GPT-3.5 Turbo (from dropdown)
  • Temperature: 0.3 (drag slider to 0.3)
  • Top-P (Nucleus Sampling): 0.9
  • Max Tokens: 1024
  • Response Format: Plain Text
Why These Values?

Temperature 0.3 keeps responses consistent and factual. GPT-3.5 Turbo balances cost and quality for customer support.

2
Pending
Configure Temperature & Top-P
Set the generation parameters:
  • Temperature: 0.3-0.5 - More consistent, factual responses
  • Top-P: 0.9 - Good balance of diversity and relevance
  • Max Tokens: 1024 - Sufficient for detailed responses
Warning

High temperature (>1.0) can cause hallucinations and inconsistent responses in customer support scenarios.

3
Pending
Enable Safety Guardrails
Check these EXACT checkboxes in the Safety & Guardrails panel:
  • ☑️ Content Filtering - MUST be checked
  • ☑️ PII Detection - MUST be checked
  • ☑️ Hallucination Guard - MUST be checked
  • ☑️ Human Escalation - MUST be checked (for complex queries)
  • ☑️ Rate Limiting - MUST be checked

All 5 checkboxes must be enabled for HIPAA compliance!

Critical

Failing to enable all guardrails will result in lab failure. Human Escalation is required for enterprise deployments.

4
Pending
Write System Prompt
Craft a system prompt that defines:
  • Bot persona and brand voice
  • Scope of allowed topics
  • Response guidelines and format
  • Escalation criteria
Pro Tip

Include 2-3 few-shot examples in your system prompt to guide the response format consistently.

5
Pending
Test Sequential Prompts & Deploy
Complete all 3 test prompts in sequence:
  1. Prompt 1: Type How do I return a defective product? and click Send
  2. Prompt 2: After response, the next prompt auto-fills: What is your warranty policy for electronics? - click Send
  3. Prompt 3: Final prompt auto-fills: Can I track my order status? - click Send

After completing all 3 prompts, click "Deploy Chatbot"

Important

You must send all 3 prompts in order. Each prompt appears automatically after the previous response. Press Enter or click the Send button.