AI & Machine Learning with Python

Course Description

We are excited to offer a hands-on and immersive AI & Machine Learning with Python internship for aspiring data scientists and machine learning enthusiasts. This internship provides a unique opportunity to gain practical experience in applying artificial intelligence and machine learning concepts to real-world projects. As an intern, you will work closely with our experienced data science team, enhancing your skills and contributing to cutting-edge AI solutions.

Responsibilities

• Data Collection and Preparation:
  • Collect, clean, and preprocess diverse datasets to ensure high-quality inputs for machine learning models.
  • Handle data transformations, feature engineering, and address data quality issues.
• Model Development:
  • Implement machine learning algorithms and AI techniques using Python libraries (such as sci-kit-learn, TensorFlow, or PyTorch).
  • Develop predictive models, classifiers, and deep learning architectures for various applications.
• Hyperparameter Tuning and Optimization:
  • Fine-tune model hyperparameters to improve performance, generalization, and accuracy.
  • Experiment with optimization techniques to enhance model efficiency and reduce computational costs.
• Model Evaluation and Validation:
  • Evaluate model performance using appropriate metrics and validate models through cross-validation techniques.
  • Identify and mitigate overfitting and underfitting issues.
• Data Visualization and Reporting:
  • Create insightful data visualizations to communicate results and findings effectively.
  • Summarize and present analysis outcomes to technical and non-technical stakeholders.
• Research and Innovation:
  • Stay up-to-date with the latest advancements in AI and machine learning research.
  • Propose innovative solutions and explore new techniques to solve complex problems.
• Collaboration and Teamwork:
  • Collaborate with fellow interns and team members to brainstorm ideas, share insights, and contribute to team projects.
  • Participate in regular team meetings, knowledge-sharing sessions, and technical discussions.
• Documentation:
  • Maintain clear and organized documentation of code, processes, and experiment results.
  • Create comprehensive documentation to facilitate knowledge transfer within the team.

Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, or a related field.
• Strong programming skills in Python and familiarity with machine learning libraries.
• Understanding of AI concepts, supervised and unsupervised learning, and neural networks.
• Knowledge of data preprocessing techniques, feature selection, and model evaluation.
• Proficiency in data visualization tools (e.g., Matplotlib, Seaborn) is a plus.
• Strong problem-solving skills and attention to detail.
• Effective communication skills to convey complex technical concepts to diverse audiences.
• Ability to work collaboratively in a dynamic and fast-paced environment.

Certification

Get industry-relevant certificates recognized by  STED Council on successful completion of the internship.