/Data-Analyst-Roadmap

Data-Analyst-Roadmap for Professionals. This roadmap contains 8 Chapters that can be completed in 8 weeks, whether you are a fresher in the field or an experienced professional who wants to transition into Data Analysis.

Primary LanguageJupyter Notebook

Data-Analyst-Roadmap

Data-Analyst-Roadmap for Students and Professionals

Notion Template Detailed Roadmap Here



This is how we are going to prepare for the Data Analyst profile:

1 - Python Programming

2 - Understanding NumPy

3 - Exploratory Data Analysis (EDA) with Pandas

4 - Data Visualization with Matplotlib and Seaborn

5 - Statistics and Statistical models

6 - Working with Different Types of Datasets

7 - Structured Query Language (SQL)

8 - Data Storytelling with Tableau or PowerBI

9 - Business Acumen and working with Business Problems

10 - Machine Learning Basics & Predictive Analytics

11 - Time Series Analysis & Forecasting

12 - Business Case Studies & Analysis

We are going to need 8 Weeks to complete each topic and be ready for the job interview.

Week 1

Chapter 1 - Python Programming & Logic Building

1 | Python Programming

Week 2

Chapter 2 - Data Analysis with Python

2 | Understanding NumPy

3 | Exploratory Data Analysis (EDA) with Pandas

4 | Data Visualization with Matplotlib and Seaborn

Week 3

Chapter 3 - Statistical Analysis and Data Analytics Projects

5 | Statistics and Statistical Models

6 | Working with Different Types of Datasets

Week 4

Chapter 4 - Database Management with SQL

7 | SQL - Structured Query Language

Week 5

Chapter 5 - Data Storytelling

8 | Data Storytelling with Tableau or PowerBI

Week 6

Chapter 6 - Business Problems

9 | Business Acumen - Working with Business Problems

Week 7

Chapter 7 - Predictive Analytics

10 | Machine Learning - Basics & Predictive Analytics

Week 8

Chapter 8 - Forecasting & Case Studies

11 | Time Series Analysis & Forecasting

12 | Business Case Studies & Analysis

What to do Next?

Resources

Data Analyst Interview

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Python🐍 Machine Learning🤖 Data Science🥼 Data Engineering🧑‍💻 Computer Vision🖥️ NLP🤍 Business Problems🚀

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