Become an expert in data analytics, machine learning, and web scraping using Python programming. Gain an in-depth understanding of the various packages in Python like NumPy, SciPy, Pandas, and Scikit-learn for performing data analysis, implementing machine learning models, and NLP. The course includes two real-life industry projects and Jupyter notebooks labs to provide an interactive and hands-on practice. This course is suited for both beginners and experienced professionals.
Python for Data Science Certification Training Course
The Data Science with Python course is designed to impart an in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. The course is packed with real-life projects, assignment, demos, and case studies to give a hands-on and practical experience to the participants.
Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization.
Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it’s modeling, and implementation using SAS.
As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis.
- Gain an in-depth understanding of data science process, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
- Install the required Python environment and other auxiliary tools and libraries
- Understand the essential concepts of Python programming like data types, tuples, lists, dicts, basic operators, and functions.
- Perform high-level mathematical computing using NumPy package and its large library of mathematical functions
- Perform scientific and technical computing using SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave.
- Perform data analysis and manipulation using data structures and tools provided in Pandas package
- Gain expertise in machine learning using the Scikit-Learn package
- Gain an in-depth understanding of supervised learning and unsupervised learning models like linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
- Use Scikit-Learn package for natural language processing
- Use matplotlib library of Python for data visualization
- Extract useful data from websites by performing web scrapping using Python
- Integrate Python with Hadoop, Spark, and MapReduce