Data Scientist Course

- Experience working on research and development tasks on Linux servers

- Practical experience with Python

- Experience using data analysis libraries (NumPy, Pandas, Matplotlib, scikit-learn, etc.)

- Visualization

- Machine learning

- Experience in data analysis using statistics, big data, machine learning, or related knowledge

- Understanding of machine learning theory (equivalent to content in PRML)

- Deep Learning Course

- Experience working on research and development tasks on Linux servers

- Practical experience with Python

- Experience using data analysis libraries (NumPy, Pandas, Matplotlib, scikit-learn, etc.)

- Coding experience using frameworks (PyTorch, Keras, etc.)

- Knowledge of basic mathematics including calculus, linear algebra, and probability statistics

- Theoretical understanding of machine learning and deep learning (computer vision, natural language processing, generative models, reinforcement learning, etc.)

- Experience implementing deep learning

- Experience in data analysis using statistics, big data, machine learning, deep learning, or related knowledge

Example Working Hours (common for each course):

As you will be working as a short-term intern, you can work according to your preferences.

Example: 1 day per month, 5-8 hours, total 5-8 hours

Example: 15 days per month, 5-8 hours, total 75-120 hours

You can also participate in post-course networking events and study sessions hosted by our AI engineers.

You'll have the opportunity to interact with project members engaged in cutting-edge research and development, providing you with a stimulating internship environment.

Depending on your preferences, you may also have the opportunity to join in ongoing curriculum development, research, and development tasks.