Design

Full Stack Data Analyst with AI

Navigate Your Career with 20+ Data Science Job Options.

Eligibility: Any Graduate/Post Graduate with Min 50% Aggregate.

Service

Unlock Your Career in 20+ Domains and 20+ Roles in Data Science

Within 4 Months ,Just by Learning 10+ Tools and 10+ Real Capstone Projects.

Simulation Based Learning

It refers to an educational approach that uses realistic, immersive simulations to teach skills, concepts, and problem-solving strategies in a controlled environment.

Real Capstone Projects

10 + Real Capstone Projects with real Data Sets from top MNC's Experts from companies like FAANG and Top MNC's like Google and Microsoft.

Job Referral Program

Access to 300+ Job Openings ,10 + Job Referrals with collaboration of 100+ Hiring Partners and consultancies.

About

Technology fueled by User Experience

Navigate Your Career with 20+ Data Science Job Options in multiple Domains and Various Roles Pan India

0

Happy Students

0 L

Highest CTC

0

Hiring Partners

PHINCO ELITE's Training Features

Top Notch Syllabus from IIM's ,IIT's

Structured,industry-Vetted Curriculum

Online Live Classes

Live Classes by Experts from FAANG Companies

Capstone Projects

Practical Experience through real Capstone Projects

Alumni Connect

Aspirational Peer group of 2000+ PHINCO Students & Alumni

Mentorships

Regular 1: 1 Mentorship from industry experts

Career Services Team

Career Support from Dedicated Recruitment Team, Alumni Network

Review

Clients' Testimonials

Rajesh Swami

"I have a B.Tech degree but felt I needed to upskill in the data science field. PHINCO ELITE's course is well-structured and highly practical, which made learning fun and effective. I was able to secure a great job with one of the best CTCs for freshers. Highly recommend this program to anyone looking to start a data science career!"

Akanksha

"As an Economics graduate, I was always fascinated by data. Joining PHINCO ELITE's Data Science and Analytics program was a game-changer. The practical training helped me develop the right skills, and I’m thrilled to have secured a job with a competitive salary package. Perfect for freshers who want to break into this field!"

Jeevana

"With a BBA degree, I knew I needed more technical skills to grow in today’s market. PHINCO ELITE's Data Science and Analytics course provided just that. The course is practical, and the trainers are very supportive. I landed a fantastic job with an excellent CTC. It’s a great course for anyone starting fresh in the industry!"

Piyush

"As an MCA graduate, I wanted to strengthen my understanding of data analytics, and PHINCO ELITE offered the perfect solution. The course is very hands-on, focusing on real-world applications. I got placed in a leading company with a great CTC. Highly recommended for freshers looking to start strong in the field of data science."

Vamsi

"After years in sales, I wanted to shift into something more analytical. PHINCO ELITE's Data Science and Analytics course gave me that opportunity. The training is very practical and industry-relevant, and I was able to secure a great job with an amazing salary package. Perfect for anyone looking to make a career switch!"

Srinath

"As someone with a background in HR, I wanted to understand data-driven decision-making better. PHINCO ELITE's Data Science course helped me gain the skills I needed. The training is thorough and practical. I’m now working in a company with a fantastic package and can see the value data brings to every industry!"

Malothu Chinna

"Coming from an MBA in Marketing background, I wanted to add data science skills to my profile. The training at PHINCO ELITE exceeded my expectations. The hands-on approach, combined with real-world projects, made it easy to grasp even complex topics. I’m happy to have secured a job with a great package as a fresher!"

Rajeev

"After completing my engineering degree, I realized my interest leaned more towards data analysis. PHINCO ELITE provided exactly the kind of practical-oriented training I was looking for. The course prepared me well, and I got placed in a top company with an excellent CTC. I would highly recommend this to freshers!"

Deepa

"I come from a commerce background (B.Com), and I wanted to switch into a more analytical role. PHINCO ELITE's Data Science and Analytics course gave me the perfect foundation to make that transition. The practical approach and real-time projects made learning easier. I landed a fantastic job with an impressive CTC, all thanks to the training!"

Krishna

"As a B.Sc. graduate, I was looking to upskill in a field that would open up more opportunities for me. Joining PHINCO ELITE's Data Science and Analytics training was one of the best decisions. The course is highly practical and industry-oriented. I'm thrilled to have secured a placement with a great company, and the CTC offered exceeded my expectations as a fresher!"

Looking for a Free Demo Session?

Book Free Demo

Program Highlights

100+ Hours of Learning from top industry experts.
Alumni Connect through webinars and seminars.
Access to LMS & Job Portals at PHINCO ELITE.
10+ Real Capstone Projects & Case Studies.
10 Certificates: Technology,Experience & Course Completion.
Free Alumni Workshops, Webinars, & Seminars.
Letter of Recommendation to the companies.

Resume Building with ATS Optimization.
LinkedIn Profile Enhancement.
Interview Question Bank with answers & mock calls.
Job Opening Notifications via Email & WhatsApp Community.
Dedicated Senior Learning Coordinator for all queries.
Dedicated SPOC throughout your career journey.
Extra 1-1 Prep Sessions before every interview.
Access to Job Portal & HRs for direct applications & communication.
Referral Drive with scheduled interviews.
Placement Services starting mid-program

Daily Academic Support via WhatsApp/Microsoft Teams.
1-1 Mentor Calls available on request.
Dedicated Senior Learning Coordinator for all queries.
Dedicated SPOC throughout your career journey

Who can Enroll?

Any Grad/PG with <50%

Freshers with Zero Experience

Non IT -IT Job Change

Career Gap

Trusted By Millions Of Learners Around The World

Curriculum

Full Stack Data Analyst with AI Introduction

Overview of Full Stack Data Science with AI 🌐
Key Roles & Responsibilities
Essential Tools & Technologies
Career Path in Data Science Fields 🤑
Roles in Data Science Field.

Excel with AI

Module 1: Exploring Data with AI🔍📊

Welcome to Excel: An Overview of the World’s Most Popular Spreadsheet Software 🖥️📈
Excel Beyond Limits 🚀📊
Mastering the Basics of Spreadsheet Navigation 🧭📋
Working on Rows and Columns 📏🔢
Looking for Exact Matches 🔍✔️
Trimming Function and Its Usage ✂️📉
Sorting the Data 🔢🔄
Nesting Functions 🏗️🔧
Data Types in Excel 📊🔠
Type Conversion in Excel 🔄🔢

Module 2: Preparing Data with AI🛠️📋

Mastering Text Functions in Excel: CONCATENATE, UPPER, LOWER, and PROPER ✍️🔤
Mastering Text Extraction in Excel: LEFT, RIGHT, and SUBSTITUTE Functions ✂️🔍
Mastering Excel’s DATE Function: Effective Techniques for Date Handling 📅🛠️
Excel DATEDIF Function (Between Two Dates) 📅↔️📅
How To Use Relative & Absolute Cell References in Excel 🔄🔒
Harnessing the Power of VLOOKUP for In-depth Insights 🔍🔎
Unleashing the Power of SUMIF Function in Excel 🔍➕

Module 3: Analyzing the Data with AI📈🔍

Mastering the COUNT, COUNTA, and COUNTBLANK Functions 🧮🔢📊
Unleashing the Power of COUNTIF Function in Excel 📊🔍
Using Excel’s Core Calculation Functions: A Practical Guide 📈🛠️
Excel Logic Functions Explained: IF, AND, and OR in Practice 🤔🔄
Organizing Data with UNIQUE and SORT Functions 🗂️🔄

SQL with AI

Module 1: SQL Fundamentals 📚💻

SQL Installation & Setup 🛠️🔧
Types of SQL Commands 📜🗂️
DDL Commands for Database and Tables 🏗️📋
SQL Constraints 🚫📊

Module 2: Data Manipulation with SQL (DML) ✏️🔄

Modifying Data in Tables ✍️📋
Retrieving Data with SQL 🔍📊

Module 3: Intermediate SQL Queries 🔍📈

Selecting Columns 📋🔢
Filtering Rows 🔍🗂️
Aggregate Functions 📊➕
Sorting & Grouping 🔢📊
Null Values ❓📉
Date and Time Functions 📅⏰
Working with Expressions 🧮🔢
Order of Execution of SQL Commands 🔄🗂️

Module 4: Joining & Combining Data 🔗🔄

Types of Joins 🔍🔗
Left & Right Join ⬅️➡️
Inner Join and Full Join 🔄🔁
Cross Join and Self Join 🔄👤
Understanding Table Relationships 🗂️🔗

Module 5: Data Preprocessing & Analysis 🔧📊

Handling Missing Values ❓📉
Handling Duplicates 🔄🚫
Data Transformation 🔄🛠️
Working with Dates and Times 📅⏳
Data Filtering and Selection 🔍📋
Analyzing Time Series Data 📈⏳
Performance Optimization ⚡🔧
Working with JSON and XML Data 📄🔢
Data Blending 🥤🔄

Module 6: Advanced SQL 🚀📊

SQL Views 👁️📋
Triggers 🚨🔄
Performance Tuning ⚙️🚀
Backup and Recovery 💾🔄
Advanced Joins 🔗🔍
Dynamic SQL 🌀🔢
Materialized Views 🗂️🔍
Database Administration Tasks 🛠️📋

Module 7: Window Functions in SQL 🪟🔢

Introduction to Window Functions 📚🪟
Analytical Functions 🔍📈
Aggregating Data Using Window Functions 📊🔢
Partitioning Data and Applying Window Functions 📋🔄

Python with AI

Module 1: Data Preprocessing with Google Play Store 📱🔧

Introduction to EDA 📊🔍
Data Cleaning 🧹🗃️
Data Visualization 📈🎨
Data Analysis 🔍📉

Module 2: Advanced Data Preprocessing with Google Play Store 📱🔍

Data Preprocessing – Removing Null Value Rows 🚫📋
Data Analysis – Numeric 🔢📊
Data Analysis – Categorical 🗂️🔍
Data Analysis – Automatic Categorical 🤖🗂️
Null Values Handling – Numeric 🔢❓
Null Values Handling – Categorical 🗂️❓
Null Values Handling Overall 🗃️❓

Module 3: Introduction to EDA 📊🔍

Introduction to EDA 📚🔎
Understanding Your Data 🤔📈

Module 4: Data Cleaning 🧹🔧

Dealing with Missing Values ❓🔍
Dealing with Duplicate Data 🔄🚫
Outliers 🚨📊
Outlier Removal Using Z-Score 🔢📉
Outlier Removal Using IQR 📏🔄
Outlier Removal Using Percentile 📈🔢
Correction of Data Type 🔄📊

Module 5: Data Visualization 📊🎨

Univariate Analysis (Non-Graphical) 📋🔍
Univariate Visualizations (Categorical) 🗂️📈
Univariate Visualizations (Numerical) 🔢📉
Bivariate Analysis (Numerical-Categorical) 🔢🗂️
Bivariate Visualizations (Categorical) 🗂️🔍
Bivariate Visualization (Numerical) 🔢🔍

Module 6: Data Analysis 🔍📊

Data Analysis with Multiple Columns 📊🔢
Data Analysis Using Conditions 🔄🔍
GroupBy in Pandas 📊🔗

Power BI with AI

📘 Section 1: Power BI – Introduction & Setup

🧠 What is Business Intelligence?
📊 What is Power BI and Why Power BI in Data Analysis
🛠️ Power BI Components
✅ Practical Applications
⬇️ Downloading Power BI & Adjusting Settings
👍 Advantages of Power BI, 👎 Disadvantages of Power BI
🔌 Types of Data Connectors in Power BI Desktop
🔄 Differences Between Microsoft Power BI and SSRS
💰 Power BI Free vs Power BI Pro vs Power BI Premium

📐 Section 2: Power BI – Query Editor

✏️ Edit Power BI App
🔄 Query Editor in Power BI for Data Transformation
🔢 Working with Numbers in Power BI
🕒 Working with Date & Time Tools
📆 Creating a Rolling Calendar in Power BI
🎛️ Conditional Columns in Power BI
📚 Grouping & Aggregating Records
🔗 Merge and Append Queries in Power BI
🔒 Manage Data Source Settings and Permissions
🔄 Data Refresh in Power BI
🏷️ Power BI Data Types
🌲 Explain Power BI Hierarchy, and How to Use it
🔗 Power BI – Excel Integration

📊 Section 3: Power BI Dashboard and Visualization

🖥️ Power BI – Dashboard
🎯 Power BI – Dashboard Actions
🎨 Adding Objects to the Power BI Report Canvas and Exploring the “Report” View
🔗 Creating Table Relationships & Data Models in Power BI
📈 Inserting Basic Charts & Visuals in Power BI
🎨 Conditional Formatting
📊 How to Add Reports to Dashboards
🎛️ Power BI Report Formatting Options
🔍 Power BI Report Filtering Options
📋 Exploring Data with Matrix Visuals
📅 Filtering with Date Slicers
📈 Adding Trend Lines & Forecasts
✏️ Editing Power BI Report Interactions
🔍 Adding Drillthrough Filters
📝 Inserting Text Cards
🖌️ How to Format a Card?
📋 Format Multi-Row Card
🗺️ Visualizing Geospatial Data with Maps
🎨 How to Format Maps
🌳 Visualizing Data with Treemaps
🎨 Format Tree Map
👥 Managing & Viewing Roles in Power BI Desktop
📋 Creating a Simple Table
🎨 Power BI – Format Table Chart
📊 Create a Stacked Column Chart
🎨 Power BI – Format Stacked Column Chart
📊 Create a 100% Stacked Column Chart
🎨 Format 100% Stacked Bar Chart
📊 Create a Stacked Bar Chart
🎨 Power BI – Format Stacked Bar Chart
📈 How to Create a Stacked Area Chart
🎨 Power BI – Format Area Chart
🧭 Create a Radial Gauge Chart
⭐ Create Key Performance Indicators (KPIs) Chart
🎨 Power BI – Format KPIs Chart
📊 Format Clustered Bar Chart
🎨 Power BI – Format Clustered Bar Chart
🌊 How to Create a Waterfall Chart?
🎨 Format Waterfall Chart
🗺️ Create a Filled Map
🎨 Format Filled Map
📈 Create a Scatter Chart
🎨 Format Scatter Chart
📉 Showing Trends with Line Charts
🎨 Power BI – Format Line Chart
🗺️ How to Create a Shape Map?
🍩 Format Donut Chart
🥧 Format Pie Chart
🎀 Format Ribbon Chart
🔣 Create an R Script Visual
📊 Line and Stacked Column Chart
🎨 Format Line and Clustered Column Chart

🧮 Section 4: DAX Introduction

📊 Data Analysis Expressions (DAX)
✏️ Intro to DAX Calculated Columns
🔢 Creating Measures Using DAX
➕ Adding Columns & DAX Measures in Power BI Desktop
🔍 Filter Context in Power BI
📚 Common DAX Function Categories
🕒 Basic Date & Time Functions
🔄 DAX Window Function
🔀 Conditional & Logical Functions
🏷️ DAX Information Functions
📝 DAX Text Functions
🔢 Index Function in Power BI
➗ DAX Trigonometric Functions
📅 DAX COUPDAY Financial Function
💰 DAX Depreciation Functions
🧮 Power BI – Distinct() Function
➕ Basic Math in Power BI
🔢 Power BI – DAX Trigonometric Functions
🔢 COUNT Functions
📅 Power BI – DAX Date Functions
📊 DAX Aggregate Functions in Power BI
📝 Power BI – DAX TEXT Functions
💰 Power BI – DAX Depreciation Functions
🔣 Power BI – DAX Bitwise Functions

🔗 Section 5: Creating Table Relationships & Data Models in Power BI

📋 What is a “Data Model”?
📚 Principles of Database Normalization
📄 Understanding Data Tables vs. Lookup Tables
🔗 Understanding Table Relationships vs. Merged Tables
🔄 Creating Table Relationships in Power BI Desktop
✏️ Managing & Editing Table Relationships | Power BI
🔄 Managing Active vs. Inactive Relationships | Power BI
🔗 Connecting Multiple Data Tables in Power BI
🔍 Understanding Filters in Power BI
🔒 Hiding Tables, Columns, and Fields from Power Pivot

Streamlit with AI

Module 1: Getting Started with Streamlit 🚀🖥️

Introduction to Streamlit 📚🔍
Streamlit Setup 🛠️📥
Basic Output Tags 🏷️📝
Inspecting the Website 🔍🌐
Text Input 📝🔠
Special Input with Buttons 🔘✨
Forms 📝📋
Integrating Scripts 🔗📜

Module 2: Page Beautification 🎨🖼️

Working with Columns 📊🗂️
Working with Tabs 📑🔄
Expander & Empty Functionalities 🔽📂
Advanced Display & Progress Options 📈🔧
Echo and Stop Commands 🔄⏹️

Module 3: Working with Data 📊🔗

Working with Media Files 🎥📁
DataFrames with Streamlit 🗃️📊
File Uploading ⬆️📂
Image Converter 🖼️🔄
Image Rotation 🔄🖼️

Module 4: Introduction to Data Visualization 📈🔍

Getting Started with Basic Plots with Streamlit 📊🔧
Plots with Matplotlib and Seaborn 📉🎨
Visualization with Plotly 📊🔍

Module 5: Deployment 🚀🌐

Deployment on Streamlit Server 🌐🖥️

Statistics

Introduction to Statistics 📊🔍

What is Statistics? ❓📚
Importance of Statistics 📈🔍
Applications of Statistics 🏥📉
Statistical Methods Overview 📋🛠️

Data and Their Types 📊🔢

Types of Data 🗃️🔠
- Quantitative Data 🔢📏
- Qualitative Data 🗂️🔡
Levels of Measurement 🎚️🔢
- Nominal 🏷️
- Ordinal 📈
- Interval 📅
- Ratio 🔢📏

Introduction to Descriptive Stats 📊📋

What is Descriptive Statistics? 📈🔍
Purpose of Descriptive Stats 🎯🔍
Types of Descriptive Statistics 📊🔢

Measures of Frequency 📊🔢

Frequency Distribution 📉📋
Frequency Tables 📊🗂️
Histograms 📈🔢
Frequency Polygons 📉🔗

Measures of Central Tendency 🧮📈

Mean ➗🔢
Median 📍🔢
Mode 🔁🔢
Comparing Measures of Central Tendency 🔄📈

Measures of Dispersion 📏📊

Range 🏆🔢
Variance 📈🔢
Standard Deviation 📊🔢
Interquartile Range (IQR) 📉🔢

Measures of Shape 📏📊

Skewness 🏞️🔢
Kurtosis 🏔️🔢
Symmetry of Distribution 🔄📈

Machine Learning Introduction

What is AI.
What is Machine Learning?.
Understanding Data and Terminology.
Types of Learning
Regression vs Classification.
Subset Of AI

Introduction to AI and Deep Learning

Introduction – Neurons vs Artificial Neural Networks.
Learning of ANN.
How to Implement and Visualize a Perceptron in Artificial Neural Networks?

4 Months

100+ Learning Hours

10+ Tools

300+ Job Openings

Real Capstone Projects

*Changes According to the Market and Time lines*

Customer Churn Analysis Tata Consultancy Services

Analyzed customer behavior to predict churn, enabling proactive retention strategies for telecom operator

Sales Forecasting Infosys

Developed predictive models to forecast sales trends and optimize inventory management.

Fraud Detection in Banking Wipro

Identified fraudulent transactions using anomaly detection techniques.

Customer Sentiment Analysis Cognizant

Leveraged natural language processing (NLP) to analyze customer reviews and improve product recommendations.

HR Attribution Analysis Accenture

Analyzed employee turnover trends and identified factors leading to attrition.

Healthcare Patient Data Analysis HCL Technologies

Evaluated patient demographics and medical history to enhance patient care and resource allocation

Energy Consumption Optimization Tech Mahindra

Monitored and optimized energy usage patterns for industrial clients.

Logistics Route Optimization Capgemini

Optimized delivery routes to minimize costs and improve efficiency.

Insurance Claim Analysis IBM India

Analyzed claims data to detect fraudulent claims and streamline processing.

Market Basket Analysis Amazon

Used association rule mining to identify product bundling opportunities.

Tools & Technologies

What are the roles ?

After completing PHINCO ELITE’s Full Data Analyst with AI course, here are various roles in Data Science Fields

Data Scientist

Data Analyst

Business Intelligence Analyst

Statistician

Data Consultant

Data Engineer

Quantitative Analyst

Data Architect

See Yourself In One Of These Roles?

Become A Data Science Expert

Upon successfully completing this program, you’ll earn a course complettion certificate along with Letter of Recommendation and Internship Certificate with global validitity.

Earn Your
Certificate

Achieve Your
Goals

Admission Process

Call Back Request

Attend Demo Call

Screening Call

Admission Letter

Take Admission

Up skill with PHINCO ELITE

Our goal is to provide you with a comprehensive educational experience. We continue to support you when you enter the workforce with a fresh outlook thanks to our unique career support services. Gain entry to more than 100 hiring partners and discover countless opportunities.

Resume Building

Interview Question Bank

2 Years of Placement Support

LinkedIn Enhancement

Mock Calls

300+ Job Openings

Our Alumni work at reputed tech organizations and promising startups

Why PHINCO ELITE

Features	PHINCO ELITE	Others
Top Notch Syllabus from IIM's and IIT's	Yes	No
Training on Real Softwares	Yes	No
Global Recognition	Yes	No
Real Capstone Projects	Yes	No
2 Years of Placement Support	Yes	No
10+ Paid Job Referrals	Yes	No
10 Certificates	Yes	No

Program Fees

Lakshya Aarambh Scholarship Seat

₹ 159000

Can get upto 70000 OFF (6/9/12/15 Months of No Cost EMI)

100 + Hours of Learning

10+ Real Softwares

10+ Real Capstone Projects

1 Year of Placement Support with Job Referrals

Resume Building + LinkedIn + Github Enhancement

10+ Paid Interviews and Referrals

No Incoming Sharing and No Extra Placement Charges

Apply Now

Popular

Premium Admission

₹ 250000 +18% GST

Can pay in 6/9/12/15 Months of No Cost EMI

100+ Hours of Learning

10 + Real Softwares

20+ Real Capstone Projects

2 Years of Placement Support with Job Referral

Dedicated Career Services Manager

Premium Access to Jobs upto 36 LPA

Unlimited Paid Interviews and Referrals

Apply Now

FAQs

What are the prerequisites for pursuing this course?

Any one from any educational background with Zero knowledge can do this program

10+2/Diploma/Graduation/PG/Freshers/Career Gaps/Homemakers/Freelancers can enrol

What is the average salary of a Data Science Associate?

The estimated total pay for a Data Science Associate is ₹8,00,000 per year, with an average salary of ₹5,00,000 per year. This number represents the median, which is the midpoint of the ranges from our proprietary Total Pay Estimate model and based on salaries collected from our users. The estimated additional pay is ₹3,00,000 per year. Additional pay could include cash bonus, commission, tips, and profit sharing.

Which industries hire Data Science Professionals the Most?

Every industry need Data Science teams to understand their products and services .Industries include Education, retail, finance, entertainment, government and public sector, higher education, sharing economy services, sales & marketing, agriculture, business intelligence, healthcare, and Banking,Media etc.,

How can i resolve my doubts while learning

We have a team called students mentors team who will be with you from the day of your joining to till you complete the program.You can reach them through our Portal SLACK

How can I get Career Support After course Completion?

Career Services Team will help you with Resume Building,Mock Calls,Interview Question Bank and we will also a Provide Access to our job Portal PHINCO ELITE JOBS where you can access unlimited Job openings

I have no tech skills.Will it work for me?

We teach from scratch. So we will cover everything from Basics to Advanced Concepts with Hands-on Experience.