This course teaches SQL syntaxes shared by many types of RDBMS. This course covers everything that a data scientist needs to know to begin working with databases today! Python – Open source, highly flexible, large number of libraries and easy-to-learn. Python for Data Science course prepares you with Python Programming capabilities for Data Manipulation, Exploratory Data Analysis and Data Visualization which are an absolute must for being a Data Science expert.
Watch Introduction Video
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32 hours of Instructor led Training
Structured Query Language (SQL) with 90% Hands-on Exercises
Analyze and Visualize data with Python libraries with 90% Hands-on Exercises
Analyze and Treat Missing Values with 90% Hands-on Exercises
Perform in-depth Exploratory data Analysis with 90% Hands-on Exercises
Test point
Using MySQL
Using Jupyter Notebooks in Anaconda
Creating user defined functions
Manipulate & Analyze data
Visualize data Using Python libraries like matplotlib and seaborn
SQL has become a very important tool for the data scientists since it is helps in fetching, updating, inserting, manipulating and modifying data from data sources like RDBMS or datawarehouses. Without having knowledge in SQL a data scientist has to rely on others to get the data for them. Python is the most common coding language typically required in data science roles. Because of its versatility, a data scientist can use Python for almost all the steps involved in data science processes. It can take various formats of data and easily import SQL tables into the Python code. Python comes with various Statistical, Machine Learning & Deep Learning libraries that can help a data scientist perform almost all tasks he/she needs.
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Government Funding
Government Funding
Fundamentals of SQL syntaxes to perform DDL, DML Indexes, sorting & complex joins with inner join, left join, right join
Learn to install Anaconda – Python distribution. Explore Python language fundamentals, including basic
syntax, variables, and types
Learn about the different data structures that Python can handle. Create and manipulate regular Python lists, tuple etc.
Learn about control and loops statements
Learn to write user defined functions. import packages for various functionalities
Manipulate and analyze dataset in Python using Pandas. Build Numpy arrays, and perform interesting calculations
Use various Python libraries to visualize data. Create and customize plots on real data
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