Data Analyst Professional Training with Python & SQL
Learn from Industry Experts | 100% Placement Assistance
Timing : 9.00 AM - 06.00 PMAbout This Course
A data analyst course typically provides an overview of the tools and techniques needed to collect, clean, analyze, and visualize data to extract meaningful insights, focusing on key skills like SQL for database querying, statistical analysis using Python, data visualization with tools like Tableau and PowerBI, and Excel proficiency, ultimately preparing students to interpret data and communicate findings to inform business decisions.
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Course Duration
4-5 Months
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Certificate
Upon Completion
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Students Enrolled
1000+
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Learning Mode
Online & Offline
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Branches
Maninagar | Gandhinagar | Kudasan | Bopal | Nikol | Mehsana | Gurukul
Course Curriculum
- Python basics - Variables, data types, operators
- Control flow - if-else, loops, functions
- Data structures - lists, tuples, dictionaries, sets
- File handling and exception handling
- Object-oriented programming (OOP) concepts
- Working with libraries and modules
- Hands-on projects and exercises
- Introduction to NumPy arrays and ndarrays
- Array indexing, slicing, and reshaping
- Mathematical operations on arrays
- Broadcasting and vectorization
- Linear algebra operations with NumPy
- Statistical functions - mean, median, std, variance
- Working with random numbers and simulations
- Introduction to Series and DataFrame
- Reading and writing data (CSV, Excel, JSON, SQL)
- Data cleaning - handling missing values, duplicates
- Data filtering, sorting, and grouping
- Merging, joining, and concatenating DataFrames
- Pivot tables and cross-tabulations
- Time series analysis with Pandas
- Introduction to Matplotlib - line plots, bar charts
- Scatter plots, histograms, and pie charts
- Customizing plots - colors, labels, legends, titles
- Subplots and figure layout management
- Introduction to Seaborn - statistical visualizations
- Heatmaps, pairplots, and distribution plots
- Creating publication-ready visualizations
- Introduction to Plotly and interactive plots
- Line charts, bar charts, and scatter plots
- 3D visualizations and surface plots
- Dashboards and interactive dash creation
- Plotly Express for quick visualizations
- Embedding plots in web applications
- Real-time data visualization with Plotly
- Introduction to databases and DBMS
- SQL basics - SELECT, INSERT, UPDATE, DELETE
- Filtering data with WHERE, AND, OR, IN, BETWEEN
- JOIN operations - INNER, LEFT, RIGHT, FULL JOIN
- Grouping data with GROUP BY and HAVING
- Subqueries and nested queries
- Window functions and advanced SQL queries
- Excel basics - formulas, functions, and formatting
- Advanced formulas - VLOOKUP, HLOOKUP, INDEX-MATCH
- PivotTables and PivotCharts for data analysis
- Data validation and conditional formatting
- Macros and VBA for automation
- Power Query for data transformation
- Dashboard creation in Excel
- Introduction to Power BI and its components
- Connecting to data sources - Excel, SQL, web
- Data transformation with Power Query
- Data modeling and relationships
- Creating interactive dashboards and reports
- DAX formulas and calculations
- Publishing and sharing reports on Power BI Service
- Real-world data analysis project
- Data collection and cleaning from multiple sources
- Exploratory data analysis (EDA)
- Building interactive dashboards
- Creating presentation and reports
- Portfolio building for job applications
- Final project presentation and feedback
