A data science project typically has multiple and numerous iterations of the same process. We often find ourselves writing the same code or updating the same function again and again. It is time-consuming and understandably frustrating.
We understand how inefficient this can be. Projects get delayed, updates are pushed back, and the entire data science project pipeline suffers.
How cool would it be to learn a few programming hacks to speed up your code and your process, and become an even more efficient data scientist?
This free course is a collection of such data science hacks, tips, and tricks! The aim of this course is to teach you key hacks to help you become a better and more efficient data science professional!
Who is this course for?
This free course is designed for data science professionals of all levels. So whether you’re a beginner or an expert, you’ll find this course helpful in your daily role.
Basic Python programming experience and data science knowledge would help but are not necessary.
- Resource Downloader
- Pandas Apply
- Extract E-mails from text
- Pandas Boolean Indexing
- Pandas Pivot Table
- Normal Distribution
- Remove Emojis from text
- Elbow method for classifier
- Pandas crosstab
- MinMax Scaler
- Feature engineering for time series data
- Dummy data for Linear Regression
- Image Augmentation
- Tokenize by Hugging Face
- Stratify - Splitting data proportionately
- Reading HTML file
- Divide Continuous and categorical data
- Pandas Profilling
- Formatting of DataFrames
- Magic function- %history
- Setting up Dark Jupyter notebook theme
- Use Jupyter-themes to change cell width
- Use parse_dates in read_csv
- Use Jupyter nbviewer to share ipynb
Ram is part of the Data Science team at Analytics Vidhya. He applies Data Science in the marketing domain. He uses his analytical acumen to optimize social media through content marketing, crafting campaigns and identifying key trends. His interests lie in the formulation of strategy using data-driven decision-making approach.
Pranav is a data scientist and Senior Editor for Analytics Vidhya. He has experience in data visualization and data science. Pranav has previously worked for a number of years in the learning and development field for a globally-known MNC. He brings a wealth of instructor experience to this course as he has taken multiple trainings on data science, statistics and presentation skills over the years. He is passionate about writing and has penned over 200 articles on data science for Analytics Vidhya.