Path to Become a Data Analyst. Learn Databases, Python, and Power BI.
From 100.83 € /h
Data is a powerful tool for decision-making in all spheres of life. Modern businesses collect data on almost everything associated with their business, and hope to use this data to get insights that will create more value for their business. However, to make sense out of such unstructured data, they need data analysts who can structure the data in their databases, and extract it whenever there is need for analysis.
I have packaged this course to take you through the whole journey of a data analyst. You will learn about databases, querying databases using SQL, modeling the data using Python, and visualizing using Power BI and Tableau.
I have packaged this course to take you through the whole journey of a data analyst. You will learn about databases, querying databases using SQL, modeling the data using Python, and visualizing using Power BI and Tableau.
Extra information
Bring your laptop
Location
Online from Kenya
About Me
I am an agile and diverse professional with experience cutting across three domains: finance, insurance, and technology. I have more than three years of experience working with data processes and operations, which have shaped my professional judgment and skills in delivering value to beginners who want to pursue the highly-sought Data Analyst career.
Education
BSc Actuarial Science with Information Technology
Maseno University, Kenya
Second Class Honors
Financial Mathematics
Institute and Faculty of Actuaries, UK
Pass
Maseno University, Kenya
Second Class Honors
Financial Mathematics
Institute and Faculty of Actuaries, UK
Pass
Experience / Qualifications
Data Analyst: SQL, Python, R, Power BI, Tableau, Excel
Actuarial professional: Insurance industry
Investment Finance: Portfolio Management
Actuarial professional: Insurance industry
Investment Finance: Portfolio Management
Age
Adults (18-64 years old)
Student level
Beginner
Duration
60 minutes
The class is taught in
English
Skills
Availability of a typical week
(GMT -05:00)
New York
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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