Introduction
On the internet, there are millions of resources that are publicly available for data enthusiasts to develop their skills. One of the best journey I would recommend to anyone is the I4G (Ingressive For Good) learning path. Why I said this?:
The journey is not just resources, it is very practical and sequential path rather than theorising your learnings.
There is a well structured community network to support you as well as interactive platform to discuss with experts in the skills.
It is time-bound to keep you on track and it is completely FREE!
In this article you’d get to know:
- About I4G: what they do, their partners, and how to apply
- What the journey looks like (I will use my personal journey: Data Analyst in SQL)
- The SQL skills I gained in my journey
About Ingressive for Good (I4G):
I4G is a non-profit EdTech committed to helping African youths to gain access to resources, training, and opportunities at no cost. Their global partners include Meta, Alphabet, Grey, DataCamp, Polygon, and MasterClass.
They have trained more than 150,000 people, $1 Million money donated, 250,000+ community network, and helped place more than 2,000 people in Jobs.
Although there are different arrays of tech skills you can benefit, in data analyst part, you have options of enrolling in any of these:
- Data Analysis with SQL — the one I applied for
- Data Analysis with Python
- Data Analysis with R
- Data Science with Python
- Data Science with R
In partnership with DataCamp Donates, these courses are available for free when selected for the 14G scholarship. The courses are virtual and self-paced lasting for 5 months. At the end of the track, you get to a professional certificate upon writing exams and successfully completed.
The application do not need prior experience nor ambiguous criteria. It is simple and amazing.
Currently, the application is closed since this cohort will elapse by July 31st, 2023. Here is a link to the application page: click here to application page
What the journey looks like for me — SQL
I have seen a lot of course but this one has my best ratings so far. What makes it amazingly different include:
- The content (course) of the track. They are sequentially crafted and touches almost all the necessary parts of SQL from beginner to advanced level. DataCamp platform allows you set up workspaces to practice your learnt skills with many datasets provided, and showcase your skill. So, it is super practical.
- The strong I4G community. In the telegram groups, you have the chance to communicate with other learners and brainstorm. There is also a group where technical experts in your track answers your questions and solve problems together. You can collaborate on DataCamp and see other people’s work while they learn.
- The helpful newsletters from I4G. The importance of the constant updates in the field of Data analytics, job opening updates, and important developments can not be overstated.
The SQL Skills I learnt in the track
The track consist of 11 courses and 1 project (I will soon solve this and share) walked me through SQL journey from basics to advanced level. The sections covered include:
NB: The track also covers Basic Statistics, Visualisation, and Data Reporting as well.
-- BASIC SQL Functions
SELECT
FROM
WHERE
HAVING
GROUP BY
ORDER BY
LIMIT;
/* we also use BETWEEN, IN, LIKE, ILIKE, IS NULL, IS NOT NULL and use
AVG(),COUNT(),MIN(),MAX(),DISTINCT() to aggregate data */
-- INTERMIDIATE AND ADVANCED SQL QUERIES
/*
JOINS - LEFT, RIGHT, INNER, and OUTER
UNION and INTERSECT
CASE WHEN THEN in combination with aggregate functions
SUBQUERIES in SELECT, FROM, WHERE statements
WINDOW FUNCTIONS AND FRAMES e.g:
OVER(), PARTITION BY(),
LAG(), LEAD(),
ROW_NUMBER(), RANK(), DENSE_RANK()
ROW_BETWEEN PRECEEDING FOLLOWING AND CURRENT ROW
CROSSTAB
EXTRACT(), date_trunc(), TRIM(), generate_series()
CONCAT(), COALESCE(), UPPER(), LOWER(), REPLACE(), REVERSE()
SUBSTRING(), POSITION(), STRPOS()
SUBSTR(), SUBSTRING()
NESTED QUERIES
CORRELATED QUERIES
PIVOTING
OLAP Operators
GROUP BY CUBE
GROUP BY ROLLUP
GROUP BY GROUPING SETS
*/
This is a summative list of queries learnt, I will provide the sample_query_codes (in practice) in my GitHub repository for the sections covered in the track.
Stay Put!
