Free Microsoft AI Courses to Boost Your Skills

2025-02-12

Microsoft is offering free AI courses with certificates to help you enhance your AI expertise. Below is a list of courses along with practical commands and codes to get you started:

1. Career Essentials in Generative AI

• Understand generative AI models, ethical considerations, and real-world impact.
• Command to install Python libraries for AI:

  pip install tensorflow keras numpy pandas
  

2. Generative AI Productivity Skills

• Learn prompt engineering and data analysis with Copilot.
• Example Python code for prompt engineering:

  import openai
  openai.api_key = 'your-api-key'
  response = openai.Completion.create(engine="text-davinci-003", prompt="Explain AI ethics", max_tokens=100)
  print(response.choices[0].text)
  

3. Artificial Intelligence for Beginners

• 12-week curriculum covering NLP, neural networks, and more.
• Command to set up a Jupyter Notebook for AI labs:

  pip install jupyterlab
  jupyter-lab
  

4. Transform Your Business with Microsoft AI

• Learn AI strategy, planning, and scaling for business leaders.
• PowerShell command to check Azure AI services:

  Get-AzResource -ResourceType "Microsoft.CognitiveServices/accounts"
  

5. AI for Managers by Microsoft

• Apply generative AI in management and enhance coaching.
• Python code to analyze team performance data:

  import pandas as pd
  data = pd.read_csv('team_performance.csv')
  print(data.describe())
  

6. Using Azure OpenAI Service

• Learn about copilots, language models, and Bing Copilot.
• Azure CLI command to deploy OpenAI model:

  az cognitiveservices account deployment create --name <deployment-name> --resource-group <resource-group> --model-name <model-name>
  

1. Build AI Apps with Azure & Power Virtual Agents

– Use Azure OpenAI and fine-tune language models.
– Command to create a Power Virtual Agent:

pac pva create --name "MyAIAgent" --environment "MyEnvironment"

8. Create Custom Machine Learning Models

• Train and run models using your data.
• Python code to train a model with TensorFlow:

  import tensorflow as tf
  model = tf.keras.Sequential([tf.keras.layers.Dense(units=1, input_shape=[1])])
  model.compile(optimizer='sgd', loss='mean_squared_error')
  model.fit(x_train, y_train, epochs=10)
  

9. Adopting Copilot for Microsoft 365

• Unlock Copilot’s benefits for work and streamline communication.
• PowerShell command to enable Copilot:

  Set-OrganizationConfig -CopilotEnabled $true
  

What Undercode Say

The free Microsoft AI courses provide an excellent opportunity to dive into the world of artificial intelligence, whether you’re a beginner or an experienced professional. By leveraging these resources, you can gain hands-on experience with cutting-edge tools and technologies. Here are some additional Linux and IT commands to enhance your learning:

• Monitor system performance while running AI models:

  top
  

• Check GPU usage for AI workloads:

  nvidia-smi
  

• Set up a Python virtual environment for AI projects:

  python3 -m venv ai-env
  source ai-env/bin/activate
  

• Install Docker to containerize AI applications:

  sudo apt-get install docker.io
  

• Deploy an AI model using Kubernetes:

  kubectl apply -f ai-deployment.yaml
  

• Use Git to version control your AI projects:

  git init
  git add .
  git commit -m "Initial AI project commit"
  

• Automate AI workflows with cron jobs:

  crontab -e
  

• Secure your AI applications with firewalls:

  sudo ufw enable
  sudo ufw allow 22
  

• Backup your AI datasets:

  rsync -av /path/to/datasets /backup/location
  

• Monitor network traffic for AI services:

  sudo tcpdump -i eth0
  

By combining these commands with the knowledge gained from the Microsoft courses, you can build, deploy, and manage AI solutions effectively. For further reading, visit the official Microsoft Learn platform: Microsoft Learn.

Remember, continuous learning and hands-on practice are key to mastering AI. Happy coding!

References:

Hackers Feeds, Undercode AI