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Mastering DataAnalyst in 12-Weeks Master Excel, Python, SQL, Tableau, and Power BI
This Data Analytics roadmap covers essential tools: Excel, Python, SQL, Tableau, and Power BI. Start by learning Excel basics, pivot tables, and charts. Then, master SQL for querying and aggregating data. Next, focus on Python for data manipulation with Pandas and visualization using Matplotlib. Finally, create interactive dashboards with Tableau and Power BI, integrating all skills into a final project and building your portfolio.
4.9 (200+ reviews)
I'M INTERESTED
Name
Phone Number
Current profile
Duration
90 Days
Fee
INR 40000/-
Mode
Online & Offline
EMI
7 months
Skill Level
Just Beginner
Duration
90 Days
Mode
Online & Offline
Fee
INR 40000/-
Skill Level
Just Beginner
Trusted by Industry Leaders
Our DataAnalytics course has empowered students to secure roles at top companies like TCS, Infosys, and Accenture.
Who Should Join?
Students and graduates looking to start a career in data analytics
Professionals seeking to enhance their data analysis skills
Business owners aiming to make data-driven decisions
Why Choose This Course?
In-Demand Skills: Master tools like Excel, SQL, and Power BI for data analysis.
Practical Learning: Gain hands-on experience with real-world datasets and projects.
Industry-Relevant Insights: Learn data visualization, trend analysis, and reporting techniques.
Career Support: Receive resume building tips, portfolio guidance, and interview preparation.
Sign on our portal and take the first step toward building your future with us!
Tools You'll Use
Overview of key tools and technologies used throughout the project or development process
MS Excel
Python
SQL
Tableau
Power BI
In Partnership with
Working with top colleges to provide essential full stack development training for student success.
ANJAC, Sivakasi
SFRC, Sivakasi
PSG, Coimbatore
In Partnership with
Working with top colleges to provide essential full stack development training for student success.
ANJAC, Sivakasi
SFRC, Sivakasi
PSG, Coimbatore
Success stories from Our Students
Hear from our past students who have successfully transformed their careers with Code Purple Academy’s Node.js training.
Dharanya Selvaraj
Accenture
In the Information Technology field, staying updated with current skills is crucial, and Code Purple Academy ensured I was well-prepared.Read More
Sanjana Suresh
Billion Face
Code Purple Academy helped me learn new skills and coding languages while also giving me valuable insight into the IT sector.Read More
Sri Hari
Coastal Aquaculture Research Institute Pvt. Ltd
Joining Code Purple Academy has been a game-changer for me. I was able to stay updated with the latest trends in the development field.Read More
Kishore
Billion Face
The Full Stack Development course at Code Purple Academy provided me with a solid foundation in both front-end and back-end technologies.Read More
Subash
ResultueTechno
Code Purple Academy provided exceptional mentor support, daily tasks, and updates, which kept me on track throughout my learning journey.Read More
Sai
TCS
Coming from an ECE background, Code Purple Academy helped me transition into coding, making me well-versed in Read More
Siva
Renault Nissan Technology & Business Centre India
Code Purple Academy played a significant role in securing my job at Renault Nissan Technology & Business Centre India.Read More
Detailed Syllabus
Modern syllabus with practical learning and interview preparation to make you job-ready.
Week 1: Introduction to Data Analytics
- Introduction to server-side development and Node.js
- Installing Node.js and setting up your environment
- Understanding the Node.js runtime and event loop
- Writing your first Node.js application
Week 2: Excel Basics and Intermediate Functions
Excel Basics:
- Workbooks, Worksheets, Cells, and Ranges.
- Basic functions: SUM, AVERAGE, COUNT, MIN, MAX.
- Sorting, Filtering, and Formatting Data.
Intermediate Excel:
- Conditional Formatting, Data Validation.
- Lookup Functions: VLOOKUP, HLOOKUP, INDEX, MATCH.
- Working with Dates and Time functions
- Basic Charts and Graphs (Bar, Line, Pie)
Week 3: Introduction to SQL
- Introduction to relational databases and SQL.
- Basic SQL commands: SELECT, FROM, WHERE, ORDER BY.
- Filtering Data with AND, OR, NOT, and comparison operators.
- Aggregation Functions: COUNT(), AVG(), SUM(), MIN(), MAX().
Week 4: Intermediate SQL
- Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN.
- Subqueries: SELECT within SELECT.
- GROUP BY and HAVING: Aggregating data by groups.
- Advanced Filtering: Working with LIKE, IN, and wildcards.
- Data Cleaning: Handling NULL values and duplicates.
Week 5: Python Basics and Data Structures
- Python syntax: Variables, Data Types (int, float, string, list, tuple, dictionary).
- Control flow: if-else, for loops, while loops.
- Functions and Modules.
- Introduction to NumPy: Arrays and basic operations.
Week 6: Pandas for Data Manipulation
- Pandas Basics: DataFrames, Series, loading data from CSVs and Excel.
- Data Cleaning: Handling missing values, duplicates, and transforming columns.
- Data Transformation: Filtering, grouping, and aggregating data.
- Data Visualization with Matplotlib & Seaborn: Basic charts (line, bar, scatter) and customizing plots.
Week 7: Getting Started with Tableau
- Installing Tableau and connecting to data sources (Excel, SQL, etc.).
- Data Preparation in Tableau: Cleaning, filtering, and transforming data.
- Basic Visualization Types: Bar charts, line charts, scatter plots, and pie charts.
- Formatting and customizing visualizations (titles, labels, colors, etc.).
Week 8: Advanced Tableau Visualizations and Dashboards
- Calculations in Tableau: Basic calculated fields (e.g., profit margins, growth rates).
- Table Calculations: Running totals, percent of total, moving averages.
- Building Interactive Dashboards: Filters, parameters, and dynamic actions.
- Storytelling with Data: Creating data-driven narratives and dashboards.
Week 9: Introduction to Power BI
- Installing Power BI and connecting to data sources (Excel, SQL, web, APIs).
- Power Query for Data Transformation: Cleaning and reshaping data before analysis.
- Basic Visualization Types in Power BI: Bar, line, pie charts, maps.
- Introduction to DAX (Data Analysis Expressions): Basic calculations (e.g., sum, average, and count).
Week 10: Advanced Power BI Features
- Data Modeling: Relationships between tables, star schema, fact and dimension tables.
- Advanced DAX: Calculated columns, measures, and time intelligence functions.
- Building and customizing Dashboards: Filters, slicers, drill-through actions.
- Publishing and Sharing Reports: Export to PDF, share via Power BI Service.
Week 11: Integrating Python, SQL, Excel, Tableau, and Power BI
- Integrating Tools: Importing data from SQL and Excel into Python, Tableau, and Power BI.
- Data Pipeline: Understanding how to clean and preprocess data in Python and SQL, then visualize and report it in Tableau/Power BI.
- Automating workflows: Using Python scripts or Excel macros to automate repetitive tasks.
- End-to-End Project: Solving a real-world problem using the entire toolset.
Week 12: Capstone Project and Portfolio Development
Capstone Project: Choose a real-world dataset (e.g., sales, marketing, or customer data)
- Clean and preprocess the data (using Python or SQL).
- Analyze the data and generate insights.
- Create a dynamic report or dashboard (using Tableau or Power BI).
Portfolio Creation: Upload your projects to GitHub, LinkedIn, or a personal website.
- Write clear documentation for each project, explaining your process and insights.
- Highlight the tools and techniques used in each project.
