Generative AI and Data Science Intern

Requirements

• Familiarity or Working knowledge in at least one programming language such as Python and its associated libraries such as TensorFlow, PyTorch, or scikit-learnis required.
  

• Familiarity or Working knowledge of backend development principles, frameworks and technologies is essential. This includes experience with server-side programming languages such as Python, Java, or Node.js and frameworks such as Flask or Django, as well as proficiency in working with databases and RESTful APIs.
  

• Familiarity or Understanding of fundamental AI concepts and techniques such as machine learning, deep learning, neural networks and architectures, data modeling, computer vision, and NLP (Natural Language Processing).
  

• Familiarity with Data Manipulation and Analysis: Proficiency in data manipulation and analysis, applicants should have basic knowledge of large datasets, performing data preprocessing, feature engineering and data visualization using visualization tools such as Google Data Studio, Power BI, Tableau, e.t.c.
  

• Familiarity with AI Ethics and Bias.
  

• Accountable via set metrics and performance indicators
  

• Analytical and problem-solving skills.
  

• Communication Skills and Teamwork.
  

• Portfolio or Demonstrable Projects that demonstrate your skills and passion for AI development. This can include personal projects, academic projects, or contributions to open-source AI projects would be an advantage for participants joining at the Level 3 (Advanced stage).