Learning Targets:

1. Classify computational problems into decision, search, optimization, and counting categories, and distinguish well-defined from ill-defined problems.

2. Determine the time complexity of an algorithm using Big O notation, identifying constant, linear, quadratic, and logarithmic growth.

3. Apply algorithm design techniques such as divide and conquer, greedy methods, and dynamic programming to a given problem.

4. Implement and trace the execution of Bubble Sort and Binary Search, comparing their efficiency.

5. Compare Breadth-First Search (BFS) and Depth-First Search (DFS) graph traversal strategies in terms of process and suitability.

Modules

Learning Targets:

1. Describe the characteristics and properties of lists, stacks, queues, trees, and graphs.

2. Perform insertion, deletion, traversal, and searching operations on the appropriate computational structures.

3. Demonstrate the LIFO principle in stacks and the FIFO principle in queues using Python code.

4. Differentiate between trees and graphs, including directed and undirected graphs, and identify their real-world applications.

5. Justify the choice of a computational structure for a given scenario based on data organization and performance considerations.

Modules

Learning Targets:

1. Calculate measures of central tendency (mean, median, mode) and measures of dispersion (variance, standard deviation) for a dataset.

2. Build a basic statistical model using linear or logistic regression and evaluate its performance against actual data.

3. Explain the principles of experimental design and the role of data collection in data science.

4. Create bar charts, line graphs, and scatterplots in MS Excel or Google Sheets, applying clear axis labels and titles.

5. Interpret a data visualization to identify patterns, trends, and conclusions relevant to a real-world problem.

Modules

Learning Targets:

1. Describe the core concepts of cloud computing, including virtualization, scalability, and on-demand access.

2. Differentiate between Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

3. Compare public, private, hybrid, and multi-cloud deployment models and identify suitable use cases for each.

4. Explain the core principles of blockchain technology, including transparency, decentralization, and the role of peer-to-peer networks.

5. Assess real-world applications of blockchain and the data security and resource implications of adopting cloud and blockchain solutions.

Modules

Learning Targets:

1. Interpret the common clauses of terms of use agreements and explain the rights and obligations they establish between a service provider and a user.

2. Identify privacy and security threats such as spyware, phishing, and pharming, and recommend strategies for preventing and mitigating them.

3. Assess the digital divide and its educational, economic, and civic implications for different social groups, with reference to local examples.

4. Recognize bias in computing systems and evaluate its impact on individuals and society.

5. Apply principles of digital citizenship and ethical conduct to use information safely and responsibly.

Modules

Learning Targets:

1. Explain the principles of Design Thinking and apply its human-centered approach to develop a business solution.

2. Develop a comprehensive business plan that includes an executive summary, market analysis, products or services, marketing strategy, and a financial plan.

3. Gather and interpret market insights using qualitative and quantitative research techniques such as customer surveys and focus groups.

4. Create and deliver a business pitch tailored to a specific audience, applying clear communication and storytelling skills.

5. Demonstrate collaboration and iteration to refine a business idea, applying key financial concepts such as budgeting and cash flow management.

Modules