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SCHEDULE

June 15, 2021
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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