Beginner to Job-Ready
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About our AI-Powered Advanced Data Analytics with A.I. M.L. Training Program -
Learn database, visualization, statistics and data analyis with ai, machine learning and projects under our experts to become an Advanced Data Analytics Professional in short duration.
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Job Opportunities -
Data Analyst, Data Analytics Developer, Power BI Developer, Data Expert etc.
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Pre-requisites -
None. Any one from IT & non IT can learn.
Connect With Experts
Syllabus
- Learn both MySQL & Adv. MySQL
- MySQL & Database Basics
- Installation
- Server
- Workbench (client)
- DDL - Data Definition Language
- Tables - Create, Alter, Drop, Auto Increment
- Constraints - Not Null, Primary Key, Unique Key, Foreign Key
- Index - Why required, Create, Drop
- DML - Data Manipulation Language
- Insert, Update, Delete & Truncate
- Transactions (T SQL)
- Commit
- Rollback
- DQL - Data Query Language (Select)
- Filters
- Operators - <, <=, >, >=, =, !=
- BETWEEN
- IN
- LIKE
- NOT
- NULL
- AND, OR, NOT
- Multi conditions filtering
- DISTINCT
- Limit, offset
- Sorting
- Ascending Order
- Descending Order
- Multi Column Sorting
- Functions
- Data, number, characters, null values etc.
- Case
- Groups
- Basics
- Grouping functions - AVG, MIN, MAX, COUNT, DISTINCT COUNT
- Grouping Filters - HAVING
- Joins
- Cartesian Product
- Equi and Non-Equi Joins
- Left Outer Join
- Right Outer Join
- Full Outer Join
- Self Join
- SET Operators
- Union
- Union All
- Intersect
- Minus
- Subquery
- Single Valued
- Multi Valued
- Views & Inline Views
- Procedures
- Programming basics - if..else, for loop
- Procedures - create, drop
- Functions
- create, drop
- Triggers
- create, drop
- Analytic (Window) Functions
- Top N Analysis
- Over() with summary functions
- Partition By Queries
- ROW_NUMBER()
- RANK()
- DENSE_RANK()
- Project
- Introduction to Python
- What is Python? Features & uses
- Python installation & IDE setup (VS Code, PyCharm, Jupyter, Anaconda)
- Running Python programs (script mode vs interactive mode)
- First program: print("Hello, World!")
- Python Basics
- Variables & Data Types (int, float, str, bool)
- Input/Output functions (print(), input())
- Comments & indentation
- Type conversion & type() function
- Operators
- Arithmetic operators (+, -, *, /, //, %, **)
- Comparison operators (==, !=, <, >, <=, >=)
- Logical operators (and, or, not)
- Assignment operators (+=, -=, etc.)
- Identity operators (is, is not)
- Membership operators (in, not in)
- Control Flow
- if, elif, else statements
- Nested conditions
- for and while loops
- break, continue, pass
- Data Structures
- Strings → indexing, slicing, methods
- Lists → create, access, update, iterate, list methods
- Tuples → immutable collections
- Sets → unique values, set operations (union, intersection)
- Dictionaries → key-value pairs, methods
- Functions
- Defining & calling functions
- Function arguments (positional, keyword, default, variable-length *args, **kwargs)
- Return values
- Lambda (anonymous functions)
- Scope (local vs global variables)
- Modules & Packages
- Importing built-in modules (math, random, datetime, os)
- Creating your own modules
- Installing external libraries with pip
- File Handling
- Opening & closing files
- Reading & writing (read(), write(), with open)
- Working with CSV and JSON files
- Exception Handling
- try, except blocks
- finally, else in exceptions
- Raising exceptions (raise)
- Custom exceptions
- Object-Oriented Programming (OOP)
- Classes & objects
- Constructors (__init__)
- Instance & class variables
- Methods (instance, class, static)
- Inheritance (single, multiple, multilevel)
- Method overriding
- Encapsulation & Abstraction
- Polymorphism
- Special methods (__str__, __len__, etc.)
- Advanced Python Concepts
- Iterators & Generators (iter(), next(), yield)
- Decorators (function decorators, @staticmethod, @classmethod)
- Regular Expressions (re module)
- Working with APIs
- Sending HTTP requests with requests
- JSON handling
- Database Connectivity
- Installation
- CRUD Operations (create, read, insert, update, delete)
- MySQL with connectors
- Python for Automation
- Automating tasks (file renaming, web scraping with BeautifulSoup)
- Working with Excel (openpyxl, pandas)
- Python for Data Science
- NumPy → arrays, vectorized operations
- Pandas → DataFrames, Series, CSV/Excel handling
- Python for Data Visualization
- Installing Matplotlib (pip install matplotlib)
- Basic Plots: Line chart, Bar chart, Pie chart
- Statistical Plots: Histogram, Scatter plot, Box plot
- Understand the Excel interface.
- Learn basic navigation and data entry.
- Excel Interface Overview
- Workbook vs. Worksheet
- Ribbon, Tabs, and Menus
- Cells, Rows, Columns
- Name Box and Formula Bar
- Basic Navigation
- Moving around the worksheet
- Selecting cells, rows, and columns
- Using the Go To command
- Data Entry and Basic Formatting
- Entering text, numbers, and dates
- Editing cell contents
- Basic formatting (font, size, color, cell alignment)
- Saving and Managing Workbooks
- Saving, opening, and closing workbookss
- Save As options (different formats)
- Summary Functions: SUM, AVERAGE, MIN, MAX, SUMIF, COUNTIF, AVERAGEIF, SUMIFS, COUNTIFS, AVERAGEIFS
- Using AutoSum
- Cell Referencing
- Relative vs. Absolute References
- Mixed References
- Organize and manage data efficiently
- Sorting and Filtering Data
- Sorting by one or multiple columns
- Applying filters to display specific data
- Using Filters using effectively
- Using Tables
- Creating and formatting tables
- Table styles and features (Total Row, Header Row)
- Data Validation:
- Creating drop-down lists
- Setting data entry rules
- Conditional formatting:
- Conditional formatting using ifs function, greater than, lower than and equal between
- Conditional formatting using colours
- Conditional formatting using colour scales, data bars & Icon sets
- Use advanced formulas and functions
- Logical Functions
- IF, AND, OR, NOT
- ** Loopkup Functions **
- VLOOKUP, VLOOKUP WITH MATCH FUNCTION, VLOOKUP WITH COLUMN & ROW FUNCTION, VLOOKUP WITH SEQUENCE FUNCTION, VLOOKUP WITH CURLY PARANTHESIS FUNCTION, VLOOKUP WITH SUMIF, SUMIFS, COUNTIF & COUNTIFS FUNCTIONS, VLOOKUP WITH MATCH FUNCTION, INDEX & MATCH, XLOOKUP, XLOOKUP WITH CONCATENATE FUNCTIONS
- Text Functions
- CONCATENATE, LEFT, RIGHT, MID, LEN
- Date and Time Functions
- TODAY, NOW, DATE, TIME, YEAR, MONTH, DAY, EOMONTH
- ** Office 365 function **
- Transpose
- Textjoin
- Sequence
- Filter
- Xlookup
- Vstack
- Hstack
- Aggregate and many more
- ** Pivoting - Analyze data using built-in Excel tools**
- Introduction to PivotTables
- What is a PivotTable?
- Benefits and uses of PivotTables
- Creating a PivotTable
- Preparing your data
- Inserting a PivotTable from various data sources
- Understanding PivotTable Components
- Rows, Columns, Values, and Filters areas
- Field List and Field Settings
- Basic PivotTable Operations
- Adding and arranging fields
- Sorting and filtering data within PivotTables
- Grouping data (by dates, numbers, etc.)
- Customizing PivotTables
- Changing the layout and style
- Using different PivotTable layouts (Compact, Outline, Tabular)
- Formatting numbers and cells
- Calculations in PivotTables
- Adding calculated fields and items
- Using summary functions (SUM, COUNT, AVERAGE, etc.)
- Showing values as percentages, differences, rankings
- PivotTable Options and Settings
- Understanding PivotTable options
- Refreshing data in PivotTables
- Changing data source
- PivotCharts
- Creating PivotCharts from PivotTables
- Customizing and formatting PivotCharts
- Understanding the relationship between PivotTables and PivotCharts
- Advanced PivotTable Techniques
- Creating dynamic PivotTables with named ranges
- Using Power Pivot to manage large data sets
- Connecting PivotTables to external data sources
- ** Create and customize advanced charts and graphs **
- Creating Charts
- Column, Bar, Line, Pie, and Combo charts
- Customizing chart elements (titles, axes, legends)
- Using Sparklines
- Creating line, column, and win/loss sparklines
- Advanced Chart Techniques
- Dynamic charts with named ranges
- Using secondary axes
- ** Automate tasks using Macros and VBA **
- Introduction to Macros
- Recording and running macros
- Macro security settings
- Basics of VBA (Recording):
- Starting with the recording Macros
- Recording of Macros
- Saving and running of Macros
- Creating Custom Functions
- Writing and using custom functions in VBA
- ** Collaborative and security features **
- Sharing and Collaboration
- Sharing workbooks
- Co-authoring and tracking changes
- Comments and notes
- Protecting Data
- Worksheet and workbook protection
- Setting permissions
- Excel Online and Mobile
- Using Excel in Office 365
- ** Power Query **
- Introduction to Power Query
- What is Power Query?
- Importance and benefits of using Power Query
- Getting Started with Power Query
- Installing and accessing Power Query
- Power Query interface and key components
- Connecting to Data Sources
- Types of data sources (Excel, databases, web, etc.)
- How to connect to different data sources
- Data Import and Shaping
- Loading data into Power Query
- Basic data transformation (filtering, sorting, removing duplicates)
- Transforming Data
- Using the Query Editor
- Applying common transformations (merging, appending, splitting columns)
- Pivoting and unpivoting columns
- Grouping data
- Data Cleaning
- Handling missing values
- Data type conversion
- Text transformations (trim, clean, replace, etc.)
- Working with Functions
- Using built-in functions
- Creating custom functions
- Parameters in Power Query
- Advanced Data Transformations
- Merging queries
- Append queries
- Using conditional columns
- Calculating and adding new columns
- ** Scenario manager**
- ** Dashboards (Project) **
- What are dashboards
- Getting data from differnt worksheets
- Display data in various charts on same sheet etc.
- ** ChattGPT (A.I. in Adv Excel)**
- Note - Since co-pilot licenseis costly, hence teaching similar topics on ChatGPT
- Introduction
- Introduction to ChatGPT by OpenAI
- Benefits of using ChatGPT with Excel
- Using ChatGPT Interface for Excel
- How to use ChatGPT without subscription
- Copy–paste workflow with Excel
- Writing effective prompts for Excel tasks
- Data Analysis Using ChatGPT using Natural Language/li>
- Formula & Function Assistance
- Generate Excel formulas using AI
- Explain existing formulas
- Fix formula errors
- Optimize and simplify formulas
- Data Cleaning with AI
- Identify missing or incorrect data
- Remove duplicates
- Standardize text, dates, and numbers
- Suggest cleaning formulas and steps
- Tables, PivotTables & Charts
- Create Excel tables
- Generate PivotTable structure using prompts
- Introduction to Power BI
- What is Power BI and Why Power BI
- Installing Power BI Desktop
- Exploring the Power BI Workflow
- Adjusting the settings of the Power BI Desktop
- Comparison of Power BI vs Other Reporting Tools
- Getting and Transforming Data with Power BI Desktop
- Connecting to different sources
- Connecting to multiple sources
- Different connecting Options(DirectQuery vs Import Data Vs Live Connection)
- Shaping and transforming data with Power Query
- Editing,Merging,Appending queries etc
- Advance Importing techniques without coding
- Data cleaning & Advance data cleaning
- Modeling with Power BI
- Introduction to Modeling
- Building Relational Models(Setup and Manage Relationships)
- Creating table relationships
- Understanding the filter flow
- Cardinality and Cross filtering
- DAX
- Understanding Dax Syntax
- Calculated Columns vs Measures
- Common Dax functions and formulae
- Understanding the evaluation context in DAX
- Visualising Data with Reports
- Creating Visualisations
- Color & Conditional Formatting
- Setting Sort Order
- Scatter & Bubble Charts & Play Axis
- Tooltips
- Slicers, Timeline Slicers & Sync Slicers
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Drill Down/Up
- Hierarchies
- Constant Lines
- Tables, Matrices & Table Conditional Formatting
- KPI's, Cards & Gauges
- Map Visualisations
- Custom Visuals
- Managing and Arranging
- Drillthrough
- Custom Report Themes
- Grouping and Binning
- Bookmarks & Buttons
- Introduction to Power BI Service
- Introduction to the Power BI Service
- Quick Tour of Power BI Service
- Connecting to Data from Power BI service
- Building Blocks of Power BI Service
- Sharing and Collaboration Tools in Power BI Service
- Sharing and Collaboration Options Overview
- Publish from Power BI Desktop
- Publish Reports to Web
- Printing and Exporting from Power BI Service
- Sharing Reports & Dashboards
- Power BI Refreshing Datasets
- What is refreshing?
- Implementation
- A.I. in Power BI
- Advance Report techniques
- Power Automate (Latest)
- Introduction
- installation
- Types of flows
- Actions
- Copy multiple excel, pdf files from one folder
- Merge PDF files together, Rename etc.
- Extract phones name and price from amazon
- Best Practices
- Mean, Median, Mode, Variance, Standard Deviation
- Skewness, Kurtosis, Correlation, Covariance
- Probability Distributions: Normal, Binomial, Poisson
- Sampling, Central Limit Theorem
- Hypothesis Testing: t-test, z-test, ANOVA, chi-square
- Confidence Intervals, p-values, Type I & II errors
- Note – Statistics part will be taken along with ML & AI as and when required
- Data Preprocessing & EDA Overview
- Handling missing values, outliers, duplicates
- Encoding (One-hot, Label), Scaling (Standard, MinMax)
- Feature engineering, selection techniques
- EDA: Univariate, Bivariate, Multivariate analysis
- Visuals: Heatmaps, Pairplots, Boxplots, Violin plots
- Supervised Learning
- Linear & Logistic Regression
- Decision Tree, Random Forest, KNN
- SVM with kernel functions
- Naive Bayes, AdaBoost, XGBoost
- Project 1: House Price Prediction
- Project 2: Email Spam Detection
- Unsupervised Learning
- K-Means, DBSCAN, Hierarchical Clustering
- Dimensionality Reduction: PCA
- Project 3: Employee Role Segmentation
- Model Evaluation & Optimization
- Metrics: Accuracy, Precision, Recall, F1, AUC, R2, RMSE
- Cross Validation, Stratified K-Fold
- Hyperparameter tuning: GridSearchCV, RandomizedSearchCV
- Imbalanced Data Handling: SMOTE, NearMiss
- Time Series Analysis Basics
- Trend, Seasonality, Noise, Stationarity
- ADF Test, ARIMA, SARIMA
- Facebook Prophet, Exponential Smoothing
- Project 4: Sales Forecasting
- 10 Months
- For Faster Job-Readiness - Early completion option in 7-8 months is available. Please connect with counsellors for more info.
- Customized Training Available
Training Examples
BOOK A FREE DEMO
(ONLINE DEMO AVAILABLE)
Google Reviews
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Shashank Patil
I have joined for power bi course conducted by aaditya sir. The course covered essential Power BI features such as data import, transformation, visualization, and DAX formulas. The material was well-structured, starting from basics to advanced topics. -
Hardik Kanitkar
Course -Data Analytics,Power BI,and Tableau. Trainer - Aaditya Sir Excellent Training given by Aaditya Sir. All the concepts were covered in detail. Highly recommended. -
Rohan Parab
If any individual wants to learn Power BI, Python and Tableau, this institute is quite good enough. Highly appreciate for the efforts taken by Aditya Sir for Power BI, Apurva madam for Python and deep sir for teaching Tableau. -
Vaibhav Patil
I would like to thank my Aditya sir for teaching us Power BI, Business Economics, and Business Knowledge in such an effective and practical way. He shared deep insights about the industry and gave us real-life examples, which made the learning process very engaging and valuable. His teaching has truly enhanced our understanding and prepared us well for real-world applications. I am very grateful for his guidance and efforts. -
Sangharsh Naik
The course emphasized hands-on practice, with numerous real-world datasets and projects. This practical approach helped me understand the application of concepts like creating dashboards in Power BI and Tableau, writing SQL queries, and performing data manipulation in Python.And I got placement in reliable consultancy pvt ltd. -
Poonam Mallah
Aditya Sir is truly a remarkable Power BI instructor. His teaching method is both interactive and insightful, making complex concepts easy to grasp. His enthusiasm for the subject is infectious, and he ensures that each student is comfortable with the material before moving forward. I have personally seen a significant improvement in my Power BI skills, thanks to his clear explanations and hands-on approach. I highly value his guidance and strongly recommend him to anyone looking to enhance their Power BI knowledge. -
Vikas Bavkar
I have joined QuickXpert for Data Analyst and till now it has been a great experience. I would like to thank shreya mam for his amazing way of clearing concepts so they are understable. I'm glad I will be completing my course at QuickXpert. -
Sapna Shayanna
I'm here for Tableau & power bi course Excellent teaching by Aaditya sir. Learned a lot. Highly recommended for data analytics. -
Dhanashree Dolas
Aditya sir is an excellent Power BI instructor, delivering complex concepts in a clear and understandable way. Their hands-on approach and real-world examples make the learning process engaging and practical. I highly recommend their course to anyone looking to enhance their data analysis skills with Power BI. -
Yogesh Khot
I join QuickExpert for Data analyst.The instructor (Pratiksha Mam) for Python is very helpful & friendly. Clear & articulate. She does not shoot down any questions but answers to the best of his abilities. Covered everything in the session, just need practice which is possible with the materials provided. -
Aishwarya Javkar
I had enrolled for Data Analyst Course. All teachers are good. I'm very happy with the teaching style of Apurva Ma'am & Aditya Thite sir. They ensures that each student is having good understanding of each topic taught by them. Very good interactive session. I attended the online lecture & Both of Sir & ma'am clear my all doubts. -
Rahul Salve
I have joined QuickXpert infotech for data analytics. First session of python was very good as I got trainer Shreya mam She explained every concept in very good manner and with technical example. Every query of mine is get cleared and also she is giving guidance even after the session is over... The start of the course is satisfactory for me... Expecting the best thing next Thank you -
Prachi Hegiste
I recently joined the quick expert infotech for Data Analytics course. And recently completed python language course. Shreya mam taught us python language. She taught paython language in easy way and clear all concepts with many examples. Thank you mam. -
Prerna Polji
I am here for Data Analytics course. Here faculty is very supportive. Power BI trainer Mr. Aditya Thite is very supportive. He teaches Power BI very perfectly and step by step. -
Pranay Karale
Superb power bi and tableau course here. Specially Aaditya sir's teaching is outstanding. Understood each & every concept industry special trainer. Highly recommended to do course from here than anywhere. Best for placements also. -
Pranay Karale
Superb power bi and tableau course here. Specially Aaditya sir's teaching is outstanding. Understood each & every concept industry special trainer. Highly recommended to do course from here than anywhere. Best for placements also. -
Safwaan Leo
Tableau course is good and I like the course and most important Aditya sirs teaching is awesome and very easy to understand..His teaching skills are good and very helpful in making each and every topic understand. -
Suhail Khatib
The faculty is great. Great place to Inroll and gain knowledge. Value for your money. Aadi sir is exceptional in teaching. Very down to earth and amazing person. Keep up the great work sir. I will definitely recommend it to all looking to enhance their tech skills.