Data Analysis Training Course
₦120,000.00
Product Highlights
Data Analysis Training Course
100 in stock
Description
Training
Type: I
·(Note: I=Individual, C=Corporate, G=Government)
This deal covers:
•Training Method: Instructor Led
Classroom/ Virtual
Schedule & Timing:
Course Duration
Weekday: 4 Months (Monday, Wednesday, Friday 10:00am – 1:00pm)
Weekend: 5 Months (Saturday 10:00am – 2:00pm)
Starting Date: November 1 , 2021
·You can call us to arrange for a schedule.
· This can also be arranged for a group of staff either at our center or your office.
·Minimum number of participants required
Free Courseware materials in soft copy
·Course materials in Detailed Practical and One on One Attention
·Certificate of Achievement awarded on request
·Deal excludes breakfast and lunch
Venue:
·Lagos: SGL Training Center. 22, Akinremi Street, 3rd floor, Anifowoshe, off Awolowo Way, Ikeja, Lagos.
Overview
Data analytics course is designed in such a way that it provides the candidates with comprehensive training to understand, study, extract, analyze, manipulate, and comprehend data to make conclusions and achieve specified data goals with the help of different software or specialized systems. Every company is searching for data-driven decision makers, and this course will teach you the skills you need to become just that. You’ll learn how to manipulate data with Microsoft Excel, SQL and Python, the fundamental languages of data science and analytics. A candidate who successfully completed and obtains a diploma course credential in Data analysis can secure opportunities job positions of data engineers, database administrators, data analysts, financial analysts, etc.
Audience
• Data analysts
• Marketing Executives
• Software Developers
• Accountants
• Statisticians
• Economists
• Financial analysts
The course scope includes following:
• Introduction to Data Science/Analysis
• Data visualization using MS Excel
• Manipulating Data set using Python
• SQL Fundamentals
• Integrating Data from user files to Microsoft/Oracle Database.
• Integrating Data from Microsoft/Oracle Database to Microsoft Excel.
• Microsoft Power BI
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