About this Masterclass
Do you want to know the most famous and fundamental libraries of Python? They are NumPy and Pandas.
NumPy is extensively used in data analysis as it provides arrays which are high-performance multidimensional objects. NumPy supports an object-oriented approach and also acts as a base for other libraries like SciPy. On the other hand, Pandas is used for data analysis as well as data cleaning. Pandas provide flexible data structures which are designed to work with structured data efficiently.
Join Mohit Uniyal in a Free Masterclass on 28th March, Tuesday at 8 PM to solve a business case study using NumPy and Pandas.
What You Will Learn From This Session
Useful Data Science Libraries
NumPy introduction
Popular NumPy functions
Pandas introduction
Popular pandas functions
Real-world use-case
Meet Mohit Uniyal (LinkedIn)
Data Scientist & Co-Creator at Coding Minutes
Mentor at TensorFlow and Google Code-in
Ex-Instructor and Product Engineer at Coding Block
About Scaler Data Science
Many professionals (like us!) enter the field of Data Science by working on toy data sets and
have no real-world knowledge of using real data. We are exposed to ‘old’ teaching methods
and are taught to ‘cram’ content. When they start working in the industry, they fail to catch up
on the skills that the industry needs because they never learned the real-world application of
using messy data and thus, end up lagging behind their peers. This leads to a loss of
confidence and stops them from accelerating in their career. This is where Scaler Data
Science solves the problems!
Scaler Data Science is a tailor-made program to master the foundations of Data Science and
Machine Learning and to take your career to the next level, via:
● A structured, guided, and industry vetted curriculum
● Live classes by faculty who have been there, done that
● Regular 1:1 mentorship from industry veterans
● Practical experience through real-life projects
● Career support via a dedicated recruitment team, alumni network, etc.
● Aspirational peer group of 3,500+ Scaler students & alumni