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SNHU
Computer Science
3 credits

SNHU CS-370: Current and Emerging Trends in Computer Science

CS-370 explores machine learning and AI as the program's emerging-trends course: neural networks, reinforcement learning, and the ethics of intelligent systems. The signature project is the pirate intelligent agent, a treasure-hunt game where you implement deep Q-learning in a provided Jupyter notebook to train an agent to find the treasure.

Fennie is independent and not affiliated with Southern New Hampshire University. This is an unofficial study guide.

What makes it hard

The math and the ML concepts arrive fast for students who haven't touched Python since the early courses, and the provided notebooks only help if you understand what the code around your section is doing. Explaining why the agent learns (exploration versus exploitation, how rewards shape behavior) is graded as heavily as making it run.

What you'll cover

  • Neural networks and Keras basics
  • Reinforcement learning
  • Deep Q-learning
  • Exploration vs. exploitation
  • AI ethics and responsible computing
  • Emerging trends analysis

The CS-370 study guide

How to study for SNHU CS-370, step by step.

  1. 1

    Refresh your Python and notebooks in week 1

    CS-370 assumes you can read and modify Python in Jupyter, and for many students it's been several Java- and C++-heavy terms since IT-140. A short refresher prevents fighting syntax and concepts simultaneously.

  2. 2

    Trace the provided notebook before writing your part

    The pirate-agent project gives you most of the code and asks you to complete the Q-learning loop. Understanding what the surrounding cells do is the difference between implementing and guessing.

  3. 3

    Learn the concepts in plain English first

    Be able to explain exploration versus exploitation and how rewards shape the agent's behavior without jargon. The written portions grade that understanding directly.

  4. 4

    Budget real time for training runs

    Training the agent takes a while and rarely works on the first attempt. Start the project week early so a failed run is information, not a crisis.

Today

Today's CS-370 plan

Preview
65 min

What a Fennie Daily Plan looks like for CS-370. Yours is built from your own syllabus and adapts every day to your deadlines and progress.

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Keep this plan free

First plan free, no card required. Fennie is independent and unaffiliated with your school.

FAQ

Is SNHU CS-370 hard?

It's conceptually the most ambitious course in the program (neural networks and reinforcement learning in 8 weeks), but the project scaffolding is generous. Students who engage with the concepts rather than just running the notebook do fine.

What is the CS-370 pirate agent project?

A treasure-hunt game where you complete a deep Q-learning implementation in a provided Jupyter notebook so the pirate agent learns to find its way through a maze to the treasure. You write the training loop and explain how and why the agent learns.

Do I need machine learning experience before CS-370?

No. The course introduces the concepts. You do need readable Python and comfort with Jupyter notebooks, so refresh those in week 1 if your recent terms have been all Java and C++.

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