AI Courses You Will Regret Not Taking in 2025

You Should Know:

1. Google to Generative AI

• URL: Google to Generative AI
• Practice Code:

  import tensorflow as tf
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense</li>
  </ul>
  
  <h1>Simple Generative Model</h1>
  
  model = Sequential([
  Dense(128, activation='relu', input_shape=(100,)),
  Dense(256, activation='relu'),
  Dense(784, activation='sigmoid')
  ])
  model.compile(optimizer='adam', loss='binary_crossentropy')
  print(model.summary())
  

  2. Google Prompting Engineering

  • URL: Google Prompting Engineering
  • Practice Command:

    </li>
    </ul>
    
    <h1>Example of using OpenAI's GPT-3 for prompt engineering</h1>
    
    openai api completions.create -m "text-davinci-003" -p "Translate the following English text to French: 'Hello, how are you?'"
    

    3. Google AI Essentials

    • URL: Google AI Essentials
    • Practice Code:

      </li>
      </ul>
      
      <h1>Basic AI Essentials: Linear Regression</h1>
      
      from sklearn.linear_model import LinearRegression
      import numpy as np
      
      X = np.array([[1], [2], [3], [4], [5]])
      y = np.array([1, 3, 2, 3, 5])
      model = LinearRegression()
      model.fit(X, y)
      print(model.predict([[6]]))
      

      4. Google Crash Course on Python

      • URL: Google Crash Course on Python
      • Practice Code:

        </li>
        </ul>
        
        <h1>Python Basics: List Comprehension</h1>
        
        squares = [x2 for x in range(10)]
        print(squares)
        

        5. IBM AI Developer

        • URL: IBM AI Developer
        • Practice Command:

          </li>
          </ul>
          
          <h1>IBM Watson AI Example</h1>
          
          curl -X POST -u "apikey:{your_api_key}" --header "Content-Type: audio/wav" --data-binary @{your_audio_file}.wav "{your_service_url}/v1/recognize"
          

          6. AI for Everyone – DeepLearning AI

          • URL: AI for Everyone – DeepLearning AI
          • Practice Code:

            </li>
            </ul>
            
            <h1>AI for Everyone: Basic Neural Network</h1>
            
            from keras.models import Sequential
            from keras.layers import Dense
            
            model = Sequential()
            model.add(Dense(10, input_dim=8, activation='relu'))
            model.add(Dense(1, activation='sigmoid'))
            model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
            print(model.summary())
            

            7. Generative AI Automation

            • URL: Generative AI Automation
            • Practice Code:

              </li>
              </ul>
              
              <h1>Generative AI: Text Generation with GPT-2</h1>
              
              from transformers import GPT2LMHeadModel, GPT2Tokenizer
              
              tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
              model = GPT2LMHeadModel.from_pretrained('gpt2')
              input_text = "Once upon a time"
              input_ids = tokenizer.encode(input_text, return_tensors='pt')
              output = model.generate(input_ids, max_length=50)
              print(tokenizer.decode(output[0], skip_special_tokens=True))
              

              1. Building with Large Language Models by DeepLearning AI

              – URL: Building with Large Language Models by DeepLearning AI
              – Practice Code:

              
              <h1>Fine-tuning a Large Language Model</h1>
              
              from transformers import TFAutoModelForCausalLM, AutoTokenizer
              
              model = TFAutoModelForCausalLM.from_pretrained('gpt2')
              tokenizer = AutoTokenizer.from_pretrained('gpt2')
              inputs = tokenizer("Hello, how are you?", return_tensors='tf')
              outputs = model(inputs)
              print(outputs)
              

              9. Prompt Engineering Basics by IBM

              • URL: Prompt Engineering Basics by IBM
              • Practice Command:

                </li>
                </ul>
                
                <h1>IBM Watson Assistant Prompt Engineering</h1>
                
                curl -X POST -u "apikey:{your_api_key}" --header "Content-Type: application/json" --data '{"input": {"text": "Hello"}}' "{your_service_url}/v1/workspaces/{your_workspace_id}/message?version=2021-06-14"
                

                10. Get Started with Python by Google

                • URL: Get Started with Python by Google
                • Practice Code:

                  </li>
                  </ul>
                  
                  <h1>Python Basics: Functions</h1>
                  
                  def greet(name):
                  return f"Hello, {name}!"
                  
                  print(greet("Alice"))
                  

                  11. Google Cybersecurity Professional Certificate

                  • URL: Google Cybersecurity Professional Certificate
                  • Practice Command:

                    </li>
                    </ul>
                    
                    <h1>Basic Linux Security Command</h1>
                    
                    sudo apt-get install ufw
                    sudo ufw enable
                    sudo ufw status verbose
                    

                    12. to SQL

                    • URL: to SQL
                    • Practice Command:

                      -- Basic SQL Query
                      SELECT * FROM employees WHERE department = 'IT';
                      

                    What Undercode Say:

                    The future of AI and cybersecurity is rapidly evolving, and staying ahead requires continuous learning and practice. The courses listed above provide a solid foundation in AI, machine learning, and cybersecurity. By practicing the provided codes and commands, you can gain hands-on experience that will be invaluable in your career. Whether you’re just starting or looking to deepen your expertise, these resources are essential for anyone in the tech industry.

                    References:

                    Reported By: Shivani Mishra – Hackers Feeds
                    Extra Hub: Undercode MoN
                    Basic Verification: Pass ✅

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