Python is increasingly becoming the language for data science. It is overtaking R in terms of adoption, it is widely known by many developers, and has a strong set of libraries such as Numpy, Pandas, scikit-learn, Matplotlib, Ipython and Scipy, to support its usage in this field.
Data Science is the emerging new hot tech field, which is an amalgamation of different disciplines including statistics, machine learning, and computer science. It’s a disruptive technology changing the face of today’s business and altering the economy of various verticals including retail, manufacturing, online ventures, and hospitality, to name a few, in a big way.
This Course is intended for all levels of Data Science professionals, both students and practitioners, starting from novice to experts. People from non-Python backgrounds can also effectively use this course, but it would be helpful if you have some prior basic programming experience.
- Explore the complete range of Data Science algorithms
- Get to know the tricks used by industry engineers to create the most accurate data science models
- Manage and use Python libraries such as numpy, scipy, scikit learn, and matplotlib effectively
- Create meaningful features to solve real-world problems
- Take a look at Advanced Regression methods for model building and variable selection
- Get a thorough understanding of the underlying concepts and implementation of Ensemble methods
- Solve real-world problems using a variety of different datasets from numerical and text data modalities
- Get accustomed to modern state-of-the art algorithms such as Gradient Boosting, Random Forest, Rotation Forest, and so on
- Python for Data Science
- Python Environments
- Data Analysis – Explore and Wrangle
- Data Analysis – Deep Dive
- Data Mining – Needle in a Haystack
- Machine Learning 1
- Machine Learning 2
- Ensemble Methods
- Growing Trees
- Large-Scale Machine Learning – Online Learning
Python Data Science Training
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