- Necessary helping tools
- Jupyter Notebook (for data exploration and testing the code)
- Google colab (jupyter notebook with free GPU)
- Kaggle (Free datasets, problems with solutions, free GPU and rich data science/ML community)
- Google cloud platform
- Github (for managing projects and getting already implemented models/code by researchers )
- Basic Programming
- A Language- Python
- Data structure (Lists, tuple, strings ,dictionaries)
- Algorithms
- OOP
- python standerd libraries
- sys (controling local machine)
- datetime
- BeautifulSoup
- Installing and managing packages
- Pip
- Conda
- Setup tools
- Library for data handling
- Numpy
- Pandas
- Re
- Visualisation libraries
- Matplotlib
- Seaborn
- Machine learning libraries
- Sklearn
- keras
- Tensorflow or Pytorch
- Web/server related libraries
- requests
- SQLAlchemy (conncting to SQL server and run queries)
- Scrapy
- Other important things for real life projects
- Basic database knowledge (SQL, Nosql)
- Hadoop
- Spark
- Basic tool for webapp development
- Flask
- Djengo
- Online cloud platforms (AWS, GCP, Azure)
- Docker (Packaging and deployment )