1 Lakh+ Learners Trained
PAN India Training & Development
ISO 9001:2015 Certified
25+ Years of Training Experience
Home/ Courses/ Advanced Data Analytics with AI

Advanced Data Analytics with AI

#1 Institute in IT Training · 25+ Years of Experience

Master Advanced Data Analytics with AI skills and take your career to the next level with comprehensive training in Advanced MS Excel, Python, NumPy, Pandas, Matplotlib, MySQL, Power BI, DAX, Power Query, Data Modeling and Artificial Intelligence.

100+ Hours5 Months Duration Offline ClassroomMode of Training Advanced Data AnalyticsMaster Program Analytics + AI StackExcel · Python · Power BI · AI
★★★★★4.9/5Google Reviews•1 Lakh+ learners
⬇ Download Brochure

Master Advanced Data Analytics with AI

The Advanced Data Analytics with AI program is a 5-month, 100+ hour offline training program covering Advanced MS Excel, Python, NumPy, Pandas, Matplotlib, MySQL, Power BI, Power Query, DAX, Data Modeling and Artificial Intelligence fundamentals.

The supplied brochure highlights tools including Excel, Python, NumPy, Pandas, Matplotlib, Seaborn, Power BI, MySQL, ChatGPT and Claude, along with NIPSTec's 25+ years of training experience, qualified and experienced trainers, job-oriented programs and industry-relevant curriculum.

Key Highlights

Advanced MS Excel

Learn advanced Excel formatting, formulas, date and time functions, filtering, validation, lookup functions, Pivot Tables, charts, What-If Analysis and security.

Python, NumPy & Pandas

Build Python programming foundations and work with NumPy arrays, Pandas Series/DataFrames and data manipulation functions.

MySQL & SQL

Cover databases, SQL queries, keys, joins, clauses, indexes, user management, privileges and MySQL functions.

Power BI & DAX

Create reports and dashboards, work with Power Query and M Language, hierarchies, drilldown, DAX, Power BI Service and data modeling.

Data Visualization

Work with Matplotlib visualizations and Power BI charts, maps, field properties, data labels and report properties.

AI Fundamentals & Generative AI

Learn AI fundamentals, machine learning, deep learning, neural networks, CNN, Generative AI, prompt engineering, ChatGPT, Gamma AI and Gemini.

Course Overview

The curriculum starts with Advanced MS Excel, then progresses through Python, NumPy and Pandas, NumPy, Pandas and Matplotlib, followed by MySQL and advanced SQL, Power BI, Power Query, DAX and data modeling, and concludes with AI fundamentals and Generative AI topics.

100+ HoursTraining Duration
5 MonthsProgram Duration
OfflineMode of Training
Data Analytics + AIProgram Focus
ExcelPythonNumPy PandasMatplotlibSeaborn MySQLPower BIPower Query DAXChatGPTClaude

Program Curriculum

The curriculum below follows the supplied Advanced Data Analytics with AI brochure, retaining its subject areas and terminology.

Module 1Advanced MS Excel⌄
  • MS Excel Introduction and Fundamentals
  • Introduction to Excel worksheet, rows, columns and cells
  • Insert and delete worksheet, row and column
  • Rename the sheet and delete multiple worksheets
  • Customizing the Ribbon
  • Currency format, Formatting Dates, Custom and special formats & Customizing Header & Footers
  • Formatting cells with number formats, Font formats, Alignment, Borders, etc.
  • Basic and advanced conditional formatting
  • Printer Properties and Page Setup for Printing
  • Insert the Logo to your worksheet while printing
  • Bar Charts, Column Charts, Pie Charts and Line Charts
  • Today, Now, Day, Month, Year, Date, Datedif, Edate, EOMonth
  • Time, Text, hour, minute and second
  • Weekday, workday, workday.INTL, networkDay, Networkdays.INTL
  • Advance Filters
  • Sorting and Filtering
  • Filtering on Text, Numbers & Colors
  • Number, Date & Time Validation
  • Text and List Validation
  • Dynamic Dropdown List Creation using Data Validation
  • Scenario Analysis & Data Tables
  • Creating, Editing, and Deleting of Names
  • Name Ranges and applying Name Ranges on cells and combinations of cells
  • Lookup/Vlookup/Hlookup/Xlookup
  • Index, Offset and Match function
  • Row, Rows, Column, Columns
  • Sort, unique
  • Average, Averaga, Sum, Count, Counta, Max, Maxa, Min, Mina
  • Countblank, Large, Small, Median, Mode, Stdev and Var
  • Dsum, Dmax, Dmin, Daverage, Dcounta
  • Pmt, Switch, Valuetotext, Yearfrac, Sequence, Sort and Filter
  • Edit Custom List
  • Consolidate data
  • Conversion of Excel files to PDF/CSV/Notepad
  • Removing Duplicates & Flash Fill
  • Comments, Freeze Panes & Shortcut Keys
  • Concatenate, Concate, Upper, Lower and Proper
  • Len, Trim, Left, Right, Mid, Find and Replace
  • Search, Substitute, Exact and Rept
  • Sumif, Sumifs, Countif, Countifs and Averageif
  • Averageifs, if, ifs, Abs, Sign and power
  • not, Ifs, Iferror and Rank
  • Round, Roundup, Rounddown and Mround
  • Creating Simple Pivot Tables
  • Basic and Advanced value Field Setting
  • Classic Pivot Table and Choosing Field
  • Filtering Pivot Tables and Charts
  • Using Slicer
  • Worksheet Protection
  • Workbook Protection
  • Column Protection
Module 2Python, NumPy & Pandas⌄
  • Introduction To Python
  • Python Features, History and Applications
  • Python Install
  • Print function
  • Data Types
  • Text type
  • Numeric type
  • Sequence type
  • Mapping type
  • Set type
  • Boolean type
  • Binary type
  • Switch case statements
  • Break statements
  • Continue statements
  • Collection Module
  • namedtuple()
  • Lists
  • Arrays
  • Tuples
  • Sets
  • Dictionary
  • OOPs
  • Classes / Objects
  • Inheritance
  • Polymorphism
  • Encapsulation
  • Abstraction
  • Python MySQL
  • MySQL Environment Setup
  • Database Connection
  • Creating New Database
  • Creating Tables
  • Insert, Read & Update Operation
  • Performing Transactions
  • NumPy Module
  • Environment Setup & Ndarray.
  • Array From Existing Data.
  • Arrays within the numerical range.
  • Broadcasting & Array Iteration.
  • Bitwise Operators, String & Mathematical Functions.
  • Statistical Functions, Sorting & Searching.
  • Pandas Module
  • Series, Series.map(), Series.std() & Series.value_counts().
  • DataFrame, DataFrame.append() & DataFrame.apply().
  • DataFrame.count()
  • DataFrame.iterrows() & DataFrame.merge()
  • DataFrame.pivot_table() & DataFrame.sort()
  • DataFrame.query() & DataFrame.shift()
  • Matplotlib Module
  • Line graph
  • Bar graph
  • Pie Chart
  • Histogram
  • Scatter plot
Module 3MySQL & Database Management⌄
  • MySQL Overview
  • DBMS & RDBMS Concepts
  • MySQL History & Features
  • MySQL Data Types & Connection
  • MySQL Data Types
  • Numeric: INT, DECIMAL, FLOAT, DOUBLE
  • String: CHAR, VARCHAR, TEXT
  • Date/Time: DATE, TIME, DATETIME, TIMESTAMP
  • Boolean
  • ENUM
  • MySQL Constraints
  • PRIMARY KEY
  • FOREIGN KEY
  • UNIQUE
  • NOT NULL
  • DEFAULT
  • CHECK
  • AUTO_INCREMENT
  • MySQL Database
  • Create Database
  • Select Database
  • Drop Database
  • Show Database
  • Table & Views
  • CREATE, ALTER & Show Table
  • Rename, Describe & TRUNCATE Table
  • DROP, Temporary & Copy Table
  • Add/Delete, Show & Rename Column
  • MySQL Queries
  • INSERT Record
  • UPDATE Record
  • DELETE Record
  • SELECT Record
  • MySQL Clauses
  • MySQL WHERE
  • MySQL DISTINCT
  • MySQL FROM
  • MySQL ORDER BY
  • MySQL GROUP BY & HAVING
  • MySQL Conditions
  • MySQL AND & OR
  • MySQL AND OR & LIKE
  • MySQL IN & NOT
  • MySQL IS NULL & IS NOT NULL
  • MySQL BETWEEN
  • MySQL Join
  • MySQL JOIN/INNER JOIN
  • MYSQL LEFT JOIN & RIGHT JOIN
  • MYSQL CROSS JOIN & SELF JOIN
  • MYSQL NATURAL JOIN
  • MySQL Indexes & User Management
  • Create, Show, Unique & Drop index
  • MYSQL Create User
  • MYSQL Drop User
  • MYSQL Show Users
  • Change User Password
  • MySQL Privileges, Control Flow Function
  • MYSQL Grant Privilege & Revoke Privilege
  • MYSQL IF() & IFNULL()
  • MYSQL NULLIF() & CASE
  • MySQL count() & sum()
  • MySQL avg(), min() & max()
  • My SQL Functions
  • MySQL String Functions
  • CONCAT()
  • UPPER()
  • LOWER()
  • LENGTH()
  • SUBSTRING()
  • REPLACE()
  • TRIM()
  • MySQL Numeric Functions
  • ROUND()
  • CEIL()
  • FLOOR()
  • ABS()
  • MOD()
  • POWER()
  • MySQL Date Functions
  • NOW()
  • CURDATE()
  • CURTIME()
  • YEAR()
  • MONTH()
  • DAY()
  • DATEDIFF()
  • DATE_FORMAT()
  • MySQL Views
  • What is a View?
  • CREATE VIEW
  • ALTER VIEW
  • DROP VIEW
  • Updatable views
  • Advantages of views
Module 4Power BI, Power Query, DAX & Data Modeling⌄
  • Power BI
  • Introduction to Power BI
  • Fundamentals of Power BI
  • Power BI - Advantages and Scalable Options
  • History - Power View, Power Query, Power Pivot
  • Business Analyst Tools, MS Cloud Tools
  • Power BI Installation and Cloud Account
  • Power BI Cloud, service, architecture and Data Access
  • Sample Reports and Visualization Controls
  • Report Design with Database Tables
  • Understanding Power BI Report Designer
  • Report Canvas, Report Pages: Creation, Renames
  • GET DATA Options and Report Fields, Filters
  • Creating Power BI reports, auto filters
  • Report Design using Databases & Queries
  • Building Home Page & Blog Section
  • Stacked bar chart, Stacked column chart, Clustered bar chart, Clustered column chart
  • Chart and map Report properties
  • Line charts, area charts, stacked area charts
  • Line and stacked row charts, line and stacked column charts
  • Waterfall chart, scatter chart, pie chart
  • Field Properties: Axis, Legend, Value, Tooltip, Colour Saturation, Filters Types
  • Power BI Design: Canvas, Visualizations and Fields
  • Import Data Options with Power BI Model, Advantages
  • Report visualizations and properties
  • Creating Customised Tables with Power BI Editor
  • Alternate Text and Tiles
  • Header (Column, Row) Properties
  • Table Styles & Alternate Row Colours - Static, Dynamic
  • Sparse, Flashy Rows, Condensed Table Reports. Focus Mode.
  • Column Headers, Column Formatting, Value Properties.
  • Data Labels: Visibility, Colour and Display Units, Precision, Position, Text Options
  • Hierarchies and Drilldown reports
  • Hierarchies and Drilldown Options
  • Hierarchy Levels and Drill Modes - Usage
  • Drill-thru Options with Tree Map and Pie Chart
  • Higher Levels and Next Level Navigation Options
  • Multi Field Aggregations and Hierarchies in Power BI
  • Toggle Options with Tabular Data. Filters.
  • Drilldown Buttons and Mouse Hover Options @ Visuals.
  • Power Query & M Language - Part 1
  • Understanding Power Query Editor - Options.
  • Power BI Interface and Query / Dataset Edits.
  • Working with Empty Tables and Load / Edits.
  • Data Imports and Query Marking in Query Editor.
  • Query Rename, Load Enable and Data Refresh Options.
  • REPLACE, REMOVE ROWS, REMOVE COL, BLANK - M Lang.
  • Column Splits and FilledUp / FilledDown Options.
  • Creating Query Groups and Query References. Usage.
  • Power Query & M Language - Part 2
  • Invoke Function and Freezing Columns.
  • Creating Reference Tables and Queries.
  • Detection and Removal of Query Datasets.
  • Blank Queries and Enumeration Value Generation.
  • Append data in different data source Merge data from multiple excel file/ or difference data source.
  • DAX Expressions
  • DAX EXPRESSIONS - Level 1.
  • Scope of Usage with DAX. Usability Options.
  • DAX Context : Row Context and Filter Context.
  • Parenthesis, Comparison, Arthmetic, Text, Logic.
  • Filter, Aggregation and Time Intelligence Functions.
  • Syntax Requirements with DAX. Differences with Excel.
  • Power BI Service & Data Modeling
  • Creating reports and dashboard.
  • Publishing reports on Power BI Service
  • Using Power BI Service for operations on reports.
  • Publishing reports to Power BI Service for sharing and collaboration.
  • Creating relationships between tables.
  • Building data models with calculated columns and measures using DAX (Data Analysis Expressions).
Module 5Artificial Intelligence Fundamentals⌄
  • What is AI
  • History of AI
  • Types of AI
  • Introduction to Machine Learning
  • Introduction to Deep Learning
  • Neural Network and Human Brain Concept
  • Neuron and Layers
  • CNN
  • Generative AI
  • Prompt Engineering
  • Output Understanding
  • ChatGPT
  • Gamma AI
  • Gemini

Tools & Technologies You'll Learn

The brochure's Tools to Master page lists Excel, Python, NumPy, Pandas, Matplotlib, Seaborn, Power BI, MySQL, ChatGPT and Claude.

ExcelPythonNumPy PandasMatplotlibSeaborn Power BIMySQLChatGPTClaude

Career-Ready Advanced Data Analytics Skills

The program combines advanced spreadsheet analytics, programming, data processing, databases, business intelligence, visualization, DAX and AI fundamentals as listed in the brochure.

Advanced Excel Analytics

Use formulas, filters, validation, lookup functions, Pivot Tables, charts, What-If Analysis and data protection features.

Python Data Processing

Build Python skills and work with collections, OOP concepts, MySQL connectivity, NumPy and Pandas.

MySQL & SQL

Manage databases and tables, write queries, use joins and clauses, work with indexes, users, privileges and aggregate functions.

Power BI Reporting

Create reports and dashboards with Power BI, visualizations, hierarchies, drilldown, Power Query, DAX and data models.

Data Visualization

Work with Matplotlib charts and Power BI visualizations, chart properties, data labels and report controls.

AI & Generative AI

Understand AI, machine learning, deep learning, neural networks, CNN, Generative AI, prompt engineering and AI tools.

Learning & Practical Support

Structured Learning

The program progresses from Excel and Python through databases, Power BI, DAX and AI fundamentals.

Offline Training

The brochure lists Offline as the mode of training for the 5-month program.

Practical Analytics

Curriculum includes practical functions, database queries, report creation, dashboards, data modeling and AI tools.

Power BI & DAX

Practice Power Query, M Language, DAX expressions, Power BI Service, relationships and calculated columns and measures.

AI Tools

The brochure's tools page includes ChatGPT and Claude, alongside the analytics technology stack.

Industry-Relevant Curriculum

The brochure highlights industry-relevant curriculum, job-oriented programs and qualified and experienced trainers.

Why Choose NIPSTec

The brochure highlights 25+ years of experience in training students and corporates, PAN India reach, trust by corporates, PSUs, government and private sector, qualified and experienced trainers, job-oriented programs and industry-relevant curriculum. It also identifies NIPSTec as an ISO 9001:2015 certified company.

25+ Years of Experience

Experience in training students and corporates.

Qualified & Experienced Trainers

Qualified and experienced trainers are highlighted by the brochure.

Industry-Relevant Curriculum

The brochure highlights industry-relevant curriculum and job-oriented programs.

Job-Oriented Programs

NIPSTec identifies its programs as job-oriented.

PAN India Reach

The brochure highlights PAN India reach and trust across multiple sectors.

ISO 9001:2015 Certified

The brochure identifies NIPSTec as an ISO 9001:2015 certified company.

Enquire About Advanced Data Analytics with AI

Submit your details to get course information, batch guidance and admission assistance.

Interested in Advanced Data Analytics with AI?

Share your details — our counsellor will call you within 24 hours.

Advanced Data Analytics with AI FAQs

Common questions about the program

What is the duration of the program?＋

The supplied brochure lists 5 Months and 100+ Hours Duration.

Is the training offline?＋

Yes. The brochure lists Offline as the mode of training.

Which tools are covered?＋

The brochure's Tools to Master page lists Excel, Python, NumPy, Pandas, Matplotlib, Seaborn, Power BI, MySQL, ChatGPT and Claude.

Does the course include Advanced MS Excel?＋

Yes. The curriculum includes advanced formatting, date/time functions, filtering, validation, What-If Analysis, lookup functions, statistical functions, import/export, Pivot Tables, charts and security.

Does the course cover Python, NumPy and Pandas?＋

Yes. Python fundamentals, data types, control statements, collections, OOPs, MySQL connectivity, NumPy and Pandas topics are included.

Does the program include MySQL and SQL?＋

Yes. DBMS/RDBMS, databases, tables, queries, keys, joins, clauses, indexes, users, privileges and MySQL functions are covered.

Does the course include Power BI and DAX?＋

Yes. Power BI reporting, visualization, hierarchies, drilldown, Power Query, M Language, DAX, Power BI Service and data modeling are included.

What AI topics are included?＋

The brochure lists AI, its history and types, Machine Learning, Deep Learning, neural networks, CNN, Generative AI, Prompt Engineering, Output Understanding, ChatGPT, Gamma AI and Gemini.

Where is the NIPSTec training location shown on the brochure?＋

The brochure's contact information lists D-82, First Floor, Malviya Nagar, New Delhi - 110017 (India).

⬇ Download Brochure