SCHEDULE
May 20, 2022
No avaliable slots
INFO
4 Weekends Data Analytics Training course is a Instructor-led and guided training being delivered during October 3 - October 25, 2020.
About this Event
4 Weekends Data Analytics training is a 4 weekends long Instructor-led and guided training with Practical Hands-On Lab exercises to be taught over 16 hours, 2 sessions per week, 2 hours per session.
The medium of instruction is English.
All Published Ticket Prices are in US Dollars.
4 Weekends Data Analytics Training Schedule
October 3, 2020 - October 25, 2020 US Pacific time
4 Weekends | 2 Hours on Saturdays, 2 Hours on Sundays every week US Pacific time
8:30 AM - 10:30 AM US Pacific time each of those days
Please click here to add your city name and check your local date and time for the first session to be held on October 3, 2020 at 8.30 AM US Pacific Time.
Features and Benefits
4 weekends, 8 sessions, 16 hours of total Instructor-led and guided training
Training material, instructor handouts and access to useful resources on the cloud provided
Practical Hands-on Lab exercises provided
Actual code and scripts provided
Real-life Scenarios
What you will learn?
What is Data Analytics
How to prepare and analyze data
When and How to use SQL for Data Analytics
When and how to use Python and Pandas for Data Analytics
Data Visualization
Who should attend
Anyone who is interested in learning Data Analytics.
Prerequisites
You don't any background in python or data analysis
Basic computer literacy
Course Outline
1. Introduction to Data Analytics
2. Learn how to prepare and analyze data
3. Data Analytics Process
Accessing Data
Importing Data
Understanding data and meaning of data
Data Cleansing
Data Transformation
Preparing for Data Visualization
4. Data Analysis and Business
Understanding business requirements and business rules
Interpreting and preparing data according to business requirements
5. Applying Database and SQL Concepts to Data for Data Analytics
Joins
6. Using Python and Pandas for Data Analytics
1) Python:
Data Types
Operators
Decision Making
Loops
String,List,Tuple functions
List Functions
Tuple functions
Functions
Date and Time
Regular Expressions
2) Pandas:
Data Types
Descriptive Statistics
Function Table/row/column wise
Iterating through Dataframe
Sorting
Series String Functions
Indexing and Selecting data
Group_By
Merging of Data, Concatenation
Date and Time
SQL statements in Pandas
7. Data Visualization Methods and Techniques
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LOCATION Riyadh - Riyadh Saudi Arabia
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