Probabilistic Machine Learning
Kevin P. Murphy, 2022

Quick Roadmaps to learn something new this year 😄

👉 Java

https://ares.decipherzone.com/blog-manager/uploads/ckeditor_Java%20Developer%20RoadMap%202022.png

👉 Python

https://t.iss.one/pythondevelopersindia/416

👉 Javascript

https://roadmap.sh/javascript

https://t.iss.one/the_programming_girls/65?single

👉 Data Analysis

https://t.iss.one/sqlspecialist/94

👉 Data Science

https://miro.medium.com/max/828/1*UQ9M5X6R1LVPzwc4bfnt9w.webp

https://t.iss.one/datasciencefun/1142

👉 Frontend development
https://i0.wp.com/css-tricks.com/wp-content/uploads/2018/07/modern-front-end-developer.png?ssl=1

https://t.iss.one/webdevcoursefree/432

👉 AI/ML

https://i.am.ai/roadmap

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍

Essential tools and skills required to become a data analyst 👇👇

### Data Analysis and Visualization:
1. Microsoft Excel: Essential for data manipulation, analysis, and basic modeling.
2. SQL (Structured Query Language): Crucial for querying databases and extracting data for analysis.
3. Tableau or Power BI: Powerful tools for creating interactive dashboards and visualizing data.

### Programming and Data Manipulation:(Optional)
4. Python: Used for data manipulation, scripting, and automation.
5. R: Useful for statistical computing, data visualization, and basic analytics.

### Statistical Analysis:
6. Statistical Software (SPSS, SAS): Tools for advanced statistical analysis and modeling.(Optional)
7. Advanced Excel Functions: Proficiency in pivot tables, VLOOKUP, statistical functions, and data cleaning techniques.

### Project Management and Collaboration:(Optional)
8. Jira or Trello: Tools for project management, task tracking, and collaboration.
9. Confluence or SharePoint: Platforms for documentation, collaboration, and knowledge sharing.

### Business Process Management:(Optional)
10. Business Process Modeling Tools (Visio, Lucidchart): Used for modeling, analyzing, and optimizing business processes.

### Additional Skills:
11. Google Analytics: Important for understanding website traffic and user behavior. (Optional)
12. CRM Systems (Salesforce, HubSpot): Knowledge of these systems aids in analyzing sales data and customer interactions.(Optional)
13. Version Control (Git): Helps manage changes in analytical projects and ensures versioning control. (Optional)

### Data Warehousing and Database Management:
14. Data Warehousing (Amazon Redshift, Google BigQuery): Knowledge of these platforms for handling large-scale datasets and optimizing queries. (Optional)

### Soft Skills:
15. Communication: Clear and concise communication of findings and recommendations.
16. Problem-Solving & Critical Thinking: Ability to analyze complex problems and derive actionable insights.

I know this list might seem extensive, so it's best to begin with mastering Excel, Power BI, and SQL. As you progress, you can gradually add other tools from the list based on specific project needs and requirements.

Here are some essential telegram channels with important resources:

❯ SQL ➟ t.iss.one/sqlanalyst
❯ Power BI ➟ @PowerBI_analyst
❯ Resources ➟ @learndataanalysis
❯ Excel ➟ t.iss.one/excel_analyst
❯ Data Portfolio ➟ @DataPortfolio

Also, try building projects & data portfolio while learning these skills. Creating data analytics projects will help you in showcasing the skills while giving job interviews.

Join @free4unow_backup for more resources

ENJOY LEARNING👍👍

Data Science Fundamentals for Python and MongoDB
David Paper, 2018

Best YouTube Playlists for Data Science

▶️ Python
🔗 Playlist Link

▶️ SQL
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▶️ Data Analysis
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▶️ Data Analyst
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▶️ Linear Algebra
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▶️ Calculus
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▶️ Statistics
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▶️ Machine Learning
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▶️ Deep Learning
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▶️ Excel Power Query
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▶️ Ruby
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▶️ Microsoft Excel
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