FREE DATA ANALYST TRAINING WITH FREE VIRTUAL INTERNSHIPS || 1000 + Reposts, Amazing 🤩
Information is power. But you need to access it first to experience its empowerment.
I was pleasantly surprised to learn that one can become a data analyst in 90 days without spending a single cent.
In this update, I share with you links to both tutorials and projects (on which you will apply the skills learnt from the tutorials 😎).
The course is designed in a way that is important for you to follow the tutorials in the order listed.
After the tutorials and projects, we present you with a list of Free Virtual Internships. Please note that for you to join the virtual Internship programs you have to create an account (for free) with the provider of the opportunity.
1. EXCEL: 12 DAYS
a) Tutorials – https://lnkd.in/dvc6fZFC
b) Projects – https://lnkd.in/ew5y5KP7
2. BASIC STATISTICS: 3 DAYS
a) Tutorials – https://lnkd.in/dtaGyj7Z
3. https://lnkd.in/dGnhCG48 has pointed out to me that these links for Power BI (20 days) have malware so I have deleted them. Oluseun Kwesi Ajayi be informed 😊.
4. SQL: 20 DAYS
a) Tutorials – https://lnkd.in/epAFJzJB
b) Projects – https://lnkd.in/eq9jqcBq
5. PYTHON: 20 DAYS
a) Tutorials – https://lnkd.in/eh4gTQQ2
b) Projects-https://lnkd.in/emzcrzTX
6. PROJECTS PORTFOLIO: 15 DAYS
a) Portfolio – https://lnkd.in/eVFWpmFg
b) Projects – https://lnkd.in/epd_9Bx8
Once you are confident about your skills, you can sign up for the following free Virtual Internships:
1. KPMG Data Analytics: https://lnkd.in/eUBvyFmd
2. BCG Data Science: https://lnkd.in/e2eC27AR
3. TATA Data Visualization: https://lnkd.in/eX-dT6HE
4. Accenture Data Analytics: https://lnkd.in/eG2RV3rZ
5. General Electric Data Analytics: https://lnkd.in/eAm6wEyT
6. PwC Power BI: https://lnkd.in/eKFs7n-n 7.
7. Quantium Data Analytics: https://lnkd.in/eT3YuB-U
Finally, you can build your resume and start applying for Jobs/engagement opportunities.
ENHANCE YOUR SKILLS FURTHER
Looking for more resources to enhance your skills? Consider completing these 39 projects and uploading them to your GIT repository: https://lnkd.in/eZ6YUdvK
As you work through each project, take the time to understand the approach used to solve it. This will not only improve your proficiency but also deepen your understanding of the subject matter. With the right approach and dedication, anyone can become a data analyst.
This was shared from LinkedIn and I found it very helpful. I hope this helps you too.