Python Programming
Deep-dive into Python programming fundamentals — OOP, file handling, modules, and libraries — building the coding foundation that powers your analytics work.
₹6,000 2 Months
Python · Power BI · MySQL · Excel
Data Analytics
Course in Howrah & Kolkata
Master Data Analytics — the high-demand skill that transforms raw numbers into powerful insights. From Python and Pandas to Power BI dashboards, MySQL databases, and Advanced Excel — become a job-ready data analyst with a comprehensive toolkit and a real-world capstone project built into the curriculum.
Python
Pandas / NumPy
Matplotlib / Seaborn
Power BI
MySQL
Advanced Excel
100
Classes
150h
Duration
42
Modules
5+
Tools
10–15
Batch Size
Course Details
What You Get
Everything you need to become a confident, job-ready Data Analyst — combining Python programming, database skills, business intelligence tools, and real-world project experience.
100 Classes · 150 Hours
A comprehensive 150-hour programme — the most thorough Data Analytics training in Howrah. Covering Python data libraries, SQL, Power BI dashboards, Advanced Excel, and a full capstone project with real datasets.
ISO & MSME Certificate
Earn a government-recognized, ISO-certified Data Analytics completion certificate — a credential that proves your skills to employers and adds genuine weight to your resume in the competitive analytics job market.
5+ Industry Tools Mastered
Python (Pandas, NumPy, Matplotlib, Seaborn), Power BI, MySQL, and Advanced Excel with VBA — the exact toolkit listed in data analyst job descriptions from every major company in India.
Small Batch Sizes
Only 10–15 students per batch ensures personal attention, faster doubt resolution, and a focused learning environment — critical for mastering complex tools like DAX, Power Query, and statistical analysis.
Bengali & Hindi Medium
Complex analytics concepts — from hypothesis testing to DAX measures and data modeling — taught clearly in Bengali and Hindi, ensuring every student genuinely understands rather than just memorizes.
Real-World Capstone Project
Apply every tool and technique to a complete end-to-end data analysis project — from data collection and cleaning through analysis, visualization, and presenting findings to stakeholders.
Full Curriculum
Course Syllabus
42 comprehensive modules — from Python fundamentals to advanced Power BI, MySQL administration, and a complete capstone project — making you a complete, industry-ready data analyst.
Modules 1–8: Python for Data Analysis
The foundation of modern data analytics. From setting up your Python environment and Jupyter Notebook to mastering Pandas for data manipulation, NumPy for numerical computing, Matplotlib and Seaborn for stunning visualizations — these modules give you the complete Python data stack used by analysts worldwide.
8 ModulesPython BasicsPandasNumPyMatplotlibSeabornWeb Scraping
01
Introduction to Data Analysis & Python EnvironmentWhat data analysis is, why Python dominates the field, installing Anaconda, setting up Jupyter Notebook, and writing your first data analysis script — end-to-end from setup to insights.
02
Data Collection and Cleaning FundamentalsData types and formats (CSV, JSON, Excel, databases), collection methods including web scraping and APIs, and essential cleaning techniques — handling missing values, duplicates, and outliers that corrupt every real-world dataset.
03
Pandas — Series, DataFrames & Data ManipulationThe most important Python library for data analysis. Creating and indexing Series and DataFrames, filtering rows and selecting columns, merging, joining, reshaping, groupby operations, and applying functions — with 50+ practice exercises on real datasets.
04
Data Visualization with MatplotlibThe foundation of Python plotting — line plots, bar charts, histograms, scatter plots, pie charts, subplots, figure and axes objects, customizing colors, labels, titles, legends, and annotations to create publication-quality charts.
05
Data Analysis with NumPyArray creation and indexing, broadcasting, vectorized mathematical operations, statistical functions (mean, median, std, percentile), linear algebra operations, and random number generation — the computational engine beneath every data science library.
06
Advanced Data Analysis TechniquesGroupby and aggregation patterns in Pandas, time series analysis (resampling, rolling windows, date parsing), pivot tables in Python, multi-level indexing, and an introduction to machine learning concepts for predictive analytics.
07
Data Visualization with SeabornStatistical visualization built on Matplotlib — distribution plots, box plots, violin plots, pair plots, heatmaps, regression plots, categorical plots, and FacetGrid for multidimensional data exploration that reveals patterns no table can show.
08
Intermediate & Advanced Data AnalysisAdvanced cleaning — handling large datasets with Pandas and Dask, string operations, regular expressions for messy text data, advanced groupby patterns, memory optimization for million-row datasets, and advanced machine learning concepts for analysis.
Modules 5–9: Exploratory Data Analysis & Statistical Analysis
The analytical core of data science. EDA is how every analyst starts — understanding the shape, distribution, and relationships in data before drawing any conclusions. Combined with statistical analysis (hypothesis testing, regression), these modules teach you to think like a data scientist, not just code like one.
5 ModulesEDADescriptive StatisticsHypothesis TestingCorrelationRegression
01
Exploratory Data Analysis — Structure & DistributionUnderstanding dataset shape (info, describe, dtypes), value counts, missing data patterns, distribution analysis with histograms, checking skewness and kurtosis — a systematic framework for understanding any new dataset from the first look.
02
Summary Statistics & Descriptive AnalysisMeasures of central tendency (mean, median, mode), measures of dispersion (range, variance, standard deviation, IQR), percentiles and quantiles, and creating comprehensive data summaries that stakeholders can actually act on.
03
Correlation Analysis & Heatmap VisualizationPearson and Spearman correlation coefficients, correlation matrices, heatmaps with Seaborn, identifying multicollinearity, and understanding the critical difference between correlation and causation — the most important concept in all of data analytics.
04
Statistical Analysis — Hypothesis Testing & p-valuesPopulation vs. sample, null and alternative hypotheses, t-tests, chi-square tests, ANOVA, p-value interpretation, confidence intervals, and statistical significance — the rigorous framework that separates data analysis from guesswork.
05
Regression Analysis & Model FittingSimple and multiple linear regression, R-squared and adjusted R-squared, residual analysis, overfitting concepts, and using regression for business forecasting — predicting sales, customer behavior, and operational metrics from historical data.
Modules 12–21: MySQL — From Basics to Administration
SQL is the universal language of data. Every company stores data in relational databases, and every analyst must query them. These modules take you from installing MySQL through advanced queries, stored procedures, performance optimization, and database administration — making you fluent in the most important data skill outside Python.
10 ModulesMySQL SetupSQL QueriesJoins & SubqueriesStored ProceduresIndexingDB Design
01
Introduction to MySQL & Relational DatabasesWhat relational databases are, the MySQL RDBMS, installing and configuring MySQL Server and MySQL Workbench, understanding tables, rows, columns, primary keys, and how databases store billions of rows efficiently.
02
MySQL Basics — Data Types, Tables & ConstraintsAll MySQL data types (INT, VARCHAR, DATE, DECIMAL, TEXT, BLOB), creating and managing databases with CREATE/DROP/ALTER, defining tables, setting primary keys, foreign keys, UNIQUE, NOT NULL, and DEFAULT constraints.
03
SQL Basics — SELECT, Filtering & SortingThe SELECT statement in full detail — choosing columns, filtering rows with WHERE (AND, OR, NOT, IN, BETWEEN, LIKE), sorting with ORDER BY, removing duplicates with DISTINCT, and limiting results with LIMIT and OFFSET.
04
Data Manipulation — INSERT, UPDATE, DELETEInserting single and multiple rows, updating records with conditional WHERE, deleting records safely, modifying table structure with ALTER TABLE (add, drop, modify columns), and working with NULL values in every operation.
05
Advanced SQL — Joins, Subqueries & AggregationsINNER, LEFT, RIGHT, FULL OUTER, and SELF joins with real business examples, correlated and non-correlated subqueries, aggregate functions (COUNT, SUM, AVG, MAX, MIN), GROUP BY, HAVING — the advanced SQL skills that distinguish senior analysts.
06
Indexes & Performance OptimizationHow B-tree indexes work, creating PRIMARY, UNIQUE, and composite indexes, using EXPLAIN to analyze query execution plans, identifying slow queries, and rewriting them for 100x speed improvements on large datasets.
07
Transactions & Concurrency ControlWhat a transaction is, COMMIT and ROLLBACK, the four ACID properties (Atomicity, Consistency, Isolation, Durability), isolation levels, deadlock detection, and locking mechanisms that keep databases consistent under concurrent load.
08
Stored Procedures, Functions & ViewsCreating reusable stored procedures with parameters and control flow, user-defined functions for complex calculations, and views that simplify repeated complex queries — the tools that separate SQL power users from beginners.
09
MySQL Administration — Users, Backup & SecurityUser account creation and privilege management (GRANT, REVOKE), backup strategies (mysqldump, binary logging), restore operations, and security best practices that protect sensitive data in production environments.
10
Database Design Best PracticesNormalization (1NF through 3NF and BCNF), denormalization for analytical workloads, entity-relationship diagrams, designing schemas that scale, data integrity constraints, and the difference between OLTP and OLAP database design.
Modules 22–30 & 42: Power BI & Advanced DAX
Power BI is the #1 business intelligence tool in India's corporate sector. These modules take you from your first dashboard to advanced DAX formulas, row-level security, and Power BI Service deployment — giving you the exact skill that makes analysts irreplaceable to management and decision-makers.
10 ModulesPower BI DesktopPower QueryData ModelingDAXDashboardsSharing & Security
01
Introduction to Power BIThe Power BI ecosystem — Power BI Desktop for building reports, Power BI Service for cloud sharing, Power BI Mobile for on-the-go dashboards. Installing Desktop, understanding the interface, and navigating between Report, Data, and Model views.
02
Data Preparation & Import with Power QueryConnecting to Excel, CSV, SQL Server, MySQL, Google Analytics, Salesforce, and web pages. Using Power Query Editor to clean, shape, merge, and append data — the ETL (Extract, Transform, Load) process that turns raw data into analysis-ready datasets.
03
Data Modeling & RelationshipsOne-to-one, one-to-many, and many-to-many relationships in the model view, managing relationship cardinality and cross-filter direction, star schema vs. snowflake schema, and building efficient data models that make DAX calculations fast.
04
Data Visualization — Charts, Maps & MatricesChoosing the right visual for every data story — bar/column charts for comparisons, line charts for trends, pie/donut for proportions, maps for geographic data, tables and matrices for detail, KPI cards for executive dashboards. Formatting and customization to presentation quality.
05
Interactive Exploration — Drill-through, Slicers & Cross-filteringDrill-down and drill-through navigation between report pages, slicers and timeline slicers for user-controlled filtering, cross-filtering between visuals, bookmarks for guided analytics experiences, and AI-powered Q&A for natural language queries.
06
Data Sharing & Collaboration on Power BI ServicePublishing reports to the Power BI Service, creating workspaces, configuring sharing permissions and access levels, embedding reports in SharePoint and Teams, and building apps for distributing dashboards across entire organizations.
07
Data Refresh & Scheduled RefreshConfiguring data source credentials for automated refresh, setting up scheduled refresh (hourly, daily, weekly), troubleshooting common refresh failures, incremental refresh for large datasets, and best practices for always-current dashboards.
08
Advanced Power BI — Row-Level Security & Custom VisualsImplementing row-level security (RLS) to restrict data visibility by user role, dynamic RLS with DAX, creating and importing custom visuals from the Power BI marketplace, and building embedded analytics for internal business applications.
09
Performance Optimization Best PracticesOptimizing report loading speed with report page optimization, reducing model size with appropriate data types, using aggregations, disabling auto date/time, and monitoring Power BI Service performance with the Performance Analyzer tool.
10
Advanced DAX — CALCULATE, SUMX & Time IntelligenceIntroduction to Data Analysis Expressions — calculated columns vs. measures, row context vs. filter context, the CALCULATE function that controls filter context, iterator functions (SUMX, AVERAGEX), time intelligence functions (DATEADD, SAMEPERIODLASTYEAR, YTD), and building KPIs that tell real business stories.
Modules 31–40: Advanced Excel for Data Analysis
Excel remains the universal business tool — every analyst must master it. These modules go far beyond basic spreadsheets into PivotTables, Power Query, Power Pivot, DAX in Excel, VBA macros, statistical analysis, and professional chart creation — making you the most capable Excel user in any room.
10 ModulesPivotTablesPower QueryPower PivotAdvanced FormulasVBA MacrosStatistical Analysis
01
Advanced Excel Features OverviewPivotTables, Power Query, Power Pivot, What-If Analysis, and review of essential functions — understanding how these tools connect to form a complete data analysis platform within Excel itself.
02
Data Cleaning & Preparation in ExcelText-to-columns, Flash Fill, removing duplicates, handling blanks with Go To Special, data validation rules, TRIM/CLEAN/SUBSTITUTE for text cleaning, and Power Query for automated, repeatable data transformation workflows.
03
Data Analysis Tools — Goal Seek, Solver & ScenariosAdvanced filtering and sorting with custom criteria, Goal Seek for reverse calculations ("what input gives this output?"), Solver for multi-variable optimization, and Scenario Manager for sensitivity analysis and business planning.
04
Statistical Analysis in ExcelDescriptive statistics with the Analysis ToolPak, calculating correlation matrices, performing t-tests and F-tests, linear regression in Excel, and interpreting statistical outputs for non-technical stakeholders — turning numbers into decisions.
05
Advanced Functions — Array Formulas, Lookup & LogicalDynamic array functions (FILTER, SORT, UNIQUE, XLOOKUP), INDEX-MATCH vs VLOOKUP, HLOOKUP, nested IFs, IFS, SWITCH, CHOOSE, IFERROR, INDIRECT, OFFSET — the advanced formula toolkit that separates expert Excel users from everyone else.
06
Data Visualization with Advanced ChartsWaterfall charts for financial analysis, Gantt charts for project timelines, box plots for statistical distributions, combo charts, bullet charts, and Sparklines — plus conditional formatting as a visualization tool for heatmaps within tables.
07
PivotTables, PivotCharts & SlicersCreating PivotTables from scratch, calculated fields and calculated items, grouping dates and numbers, PivotCharts for dynamic visualization, Slicers for interactive filtering, Timelines for date-based analysis — making any stakeholder self-service on your data.
08
Data Modeling with Power Pivot & DAX in ExcelLoading multiple tables into the Power Pivot Data Model, creating relationships between tables, writing DAX measures (SUM, CALCULATE, DIVIDE, RELATED), and building PivotTables from the data model — bringing Power BI-level analytics into Excel.
09
Automating Tasks with Macros & VBARecording macros for repetitive tasks, editing macro code in the VBA editor, writing custom Sub procedures and Function procedures, working with Ranges and Worksheets programmatically, and building user forms for data entry — saving hours of manual work every week.
10
Data Analysis Case StudiesApplying all advanced Excel techniques to real business scenarios — sales analysis dashboards, financial reporting automation, HR data analysis, inventory tracking with VBA, and dynamic reporting systems that update automatically when new data arrives.
Modules 41–42: Capstone Project & Advanced Analytics
Where everything comes together. The capstone module challenges you to complete a full end-to-end data analysis project — identifying a real business problem, collecting and cleaning data, performing EDA and statistical analysis, building visualizations in Python and Power BI, querying with SQL, and presenting findings professionally. This is the portfolio piece that gets you hired.
2 ModulesEnd-to-End ProjectProblem DefinitionFull PipelinePresentation SkillsPortfolio Ready
01
Capstone Project — Problem Definition & Data CollectionIdentifying a meaningful research question from a real-world domain (e-commerce, healthcare, finance, or HR), sourcing an appropriate dataset, planning the analysis approach, and setting up the complete project environment with Python, SQL, and Power BI.
02
Data Cleaning & Exploratory Analysis PhaseApplying all cleaning techniques to the raw dataset — handling missing values, outliers, inconsistent formats, and duplicate records — then conducting thorough EDA with Python to uncover initial patterns, distributions, and correlations.
03
Statistical Analysis & Hypothesis Testing PhaseFormulating and testing hypotheses about the data, performing regression analysis, calculating confidence intervals, and drawing statistically valid conclusions that can withstand scrutiny from technical reviewers.
04
Database Integration — Storing & Querying with MySQLImporting the cleaned dataset into MySQL, designing an appropriate schema, writing analytical SQL queries to answer business questions, creating stored procedures for repeated analysis, and connecting the MySQL data to Power BI.
05
Power BI Dashboard DevelopmentBuilding a multi-page Power BI dashboard from the project data — with appropriate visuals for each insight, interactive slicers, drill-through pages, DAX measures for calculated KPIs, and a polished design suitable for executive presentation.
06
Final Presentation & Portfolio SubmissionStructuring the findings as a professional presentation — executive summary, methodology, key insights, business recommendations, and limitations. Presenting to the class and instructor for feedback, and packaging the project as a portfolio piece for job applications.
07
Advanced Analytics with DAX Deep DiveA dedicated module on advanced DAX patterns — virtual tables with SUMMARIZE and ADDCOLUMNS, complex CALCULATE scenarios, semi-additive measures, parent-child hierarchies, and building a complete DAX measure library for the capstone project.
What You'll Learn
Learning Outcomes
Graduate as a complete data analyst — capable of collecting, cleaning, analyzing, visualizing, and presenting data with Python, SQL, Power BI, and Excel to drive real business decisions.
Analyze Data with Python
Use Pandas for data manipulation, NumPy for numerical computing, and Matplotlib/Seaborn for visualization — automating analysis that would take days in Excel in just minutes of Python code.
Conduct Rigorous EDA
Systematically explore any new dataset — understanding distributions, spotting anomalies, identifying correlations, and generating hypotheses that guide deeper analysis and drive business insight.
Query & Manage Databases
Write complex SQL queries with joins, subqueries, and aggregations — design efficient MySQL schemas, create stored procedures, and connect databases to Python and Power BI for seamless data pipelines.
Build Power BI Dashboards
Design and publish professional Power BI dashboards with DAX measures, interactive slicers, drill-through pages, and row-level security — turning data into visual stories that executives and stakeholders actually use.
Master Advanced Excel
Build dynamic reports with PivotTables and Power Pivot, automate workflows with VBA macros, perform statistical analysis with the Analysis ToolPak, and use advanced formulas like XLOOKUP and dynamic arrays.
Deliver End-to-End Analytics Projects
Execute a complete analytics project — from defining the business question through data collection, cleaning, analysis, visualization, and professional presentation — with a portfolio piece ready for job interviews.
Who Should Join?
This Course Is For You
Data analytics is the fastest-growing career in India. Whether you're a student, professional, or business owner — the ability to turn data into decisions is the most valuable skill you can acquire right now.
🎓
College Students
BCA, MCA, BTech, BSc IT, MBA, and BBA students who want to enter the data field. Data analyst roles pay 30–80% more than general IT roles — and this course gives you every tool hiring managers are asking for in Kolkata and beyond.
💼
Working Professionals
Accountants, marketing executives, HR managers, and operations professionals who work with data every day — learning to analyze it properly with Python, Power BI, and advanced Excel will make you invaluable in your current role and open new career paths.
📊
Aspiring Data Analysts
Anyone who wants to start a career as a data analyst, business analyst, or BI developer. Data analytics is one of the top 5 in-demand careers in India — and this course gives you the complete toolkit to apply, interview, and land the role.
FAQ
Frequently Asked Questions
What is the fee for the Data Analytics course at PBA Institute?
The batch class fee is ₹15,000 for the complete course — 100 classes, 150 hours, 42 modules covering Python, Power BI, MySQL, Advanced Excel, DAX, and a full capstone project. One-to-One personalized sessions are available at a higher fee with a fully flexible schedule. Both include study materials, software installation support, and an ISO-certified government-recognized certificate.
Do I need programming knowledge before joining?
No prior programming experience is required. The course begins with Python environment setup and fundamentals before moving into Pandas, NumPy, and visualization libraries. Similarly, MySQL and Excel modules start from zero. PBA Institute teaches in Bengali and Hindi, ensuring no language barrier slows you down. All you need is the willingness to learn and a laptop.
What tools and technologies are covered in the Data Analytics course?
The course covers five major tool categories: Python (Pandas, NumPy, Matplotlib, Seaborn, web scraping, Dask); Exploratory Data Analysis and Statistical Analysis (EDA, hypothesis testing, regression); MySQL (from installation through advanced SQL, stored procedures, indexing, and DB administration); Power BI (Desktop, Service, Power Query, DAX, row-level security, dashboards); and Advanced Excel (PivotTables, Power Query, Power Pivot, DAX in Excel, VBA macros, advanced formulas). All tools are covered with practical exercises and real datasets.
Is the Data Analytics course available online?
Yes. PBA Institute offers both online and in-person classes with the same instructor, same curriculum, and the same live coding and analysis sessions as the Howrah campus. Online students participate in live sessions, get their code and dashboards reviewed in real time, and receive the same ISO-certified certificate as classroom students.
What jobs can I get after completing this Data Analytics course?
Completing this course prepares you for roles including: Data Analyst, Business Analyst, BI Analyst, MIS Analyst, Reporting Analyst, SQL Developer, Power BI Developer, and Python Data Analyst. These roles are available across banking, e-commerce, healthcare, manufacturing, IT services, and consulting — and starting salaries in Kolkata typically range from ₹3–8 lakhs per annum for freshers with this skill set.
What certificate will I receive after completing the Data Analytics course?
You receive a course completion certificate from PBA Institute — ISO 9001:2015 Certified and MSME Government Registered. This is a recognized, government-backed credential that carries genuine weight when applying for data analyst, MIS analyst, BI developer, or business analyst roles anywhere in India. Unlike many private institute certificates, the MSME registration gives it official government standing.
Turn Data Into Your Career
Ready to Master Data Analytics?
Join PBA Institute's Data Analytics course in Howrah. Master Python, Power BI, MySQL, and Advanced Excel across 100 classes and 150 hours. Earn an ISO certificate and become the data analyst that every company in India is actively hiring for right now.
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