Seats will be confirmed on first-come-first-serve basis Total Seat: 60
As per the Economic Times, the demand for Data professionals grew by 417%, while the supply has seen just a 19% increase. This demand-supply gap for Data Science professionals make it one of the most lucrative career options.
Intel survey report predicts that 70% of Indian companies will deploy AI enabled solutions by the end of 2019. India will create more jobs for AI and Robotics experts.
In today’s world, the knowledge on discovering insights and interpreting data is not enough. The data should result in business gains, and should be able to predict future business outcomes accurately.
Data Science with Python
This Data Science with Python course will establish your mastery of Data Science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and gain in-depth knowledge in data analytics, Machine Learning, data visualization, web scraping, and natural language processing. Python is a required skill for many Data Science positions, so jump start your career with this interactive, hands-on course
(1)Key Learning Objectives Gain an in-depth understanding of Data Science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics
(2)Install the required Python environment and other auxiliary tools and libraries
(3)Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
(4)Perform high-level mathematical computing using the NumPy package and its vast library of mathematical functions
(5)Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
(6)Perform data analysis and manipulation using data structures and tools provided in the Pandas package
(7)Gain expertise in Machine Learning using the Scikit-Learn package
(8)Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline 9 10 11 12 21 |
(9)Use the Scikit-Learn package for natural language processing
(10)Use the matplotlib library of Python for data visualization
(11)Extract useful data from websites by performing web scraping using Python
(12)Integrate Python with Hadoop, Spark, and MapReduce
(1)Lesson 1 – Data Science Overview
(2)Lesson 2: Data Analytics Overview
(3)Lesson 3: Statistical Analysis and Business Applications
(4)Lesson 4: Python Environment Setup and Essentials
(5)Lesson 5: Mathematical Computing with Python (NumPy)
(6)Lesson 6 – Scientific computing with Python (Scipy)
(7)Lesson 7 – Data Manipulation with Pandas
(8)Lesson 8 – Machine Learning with Scikit–Learn
(9)Lesson 9 – Natural Language Processing with Scikit Learn
(10)Lesson 10 – Data Visualization in Python using matplotlib This lesson teaches you to visualize data in python using matplotlib and plot them.
(11)Lesson 11 – Web Scraping with BeautifulSoup Lesson 12 – Python integrati