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Data Science

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  • Module 1: Introduction to AI, Data Science & Machine Learning

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    • What is Artificial Intelligence
    • What is Data Science & Machine Learning
    • Applications of Data Science in industries
    • Phases of Data Science projects
    • Role of Python in Data Analytics
    • Machine Learning workflow
    • Regression vs Classification
    • Features, Labels and Classes

  • Module 2: Python Essentials (Core)

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    • Anaconda Installation
    • Python IDEs (Jupyter Notebook, Spyder)
    • Python Basics and Syntax
    • Data Types (int, float, string, boolean)
    • Lists, Tuples, Dictionaries
    • Strings and String Methods
    • Operators and Control Structures
    • Loops and Functions

  • Module 3: Data Handling with Python

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    • Introduction to NumPy
    • Introduction to Pandas
    • Importing data (CSV, Excel, TXT)
    • Exporting data to various formats
    • Basic data operations using Pandas

  • Module 4: Data Preprocessing

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    • Data cleaning techniques
    • Handling missing values
    • Removing duplicates
    • Data transformation and normalization
    • Merging and joining datasets

  • Module 5: Exploratory Data Analysis (EDA)

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    • Descriptive statistics
    • Data summarization techniques
    • Frequency distribution
    • Identifying patterns and trends
    • Correlation and covariance

  • Module 6: Data Visualization

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    • Visualization basics
    • Matplotlib library
    • Seaborn library
    • Bar, Line, Pie charts
    • Histogram, Boxplot, Scatter plot

  • Module 7: Machine Learning Fundamentals

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    • Introduction to Machine Learning
    • Types of Machine Learning (Supervised, Unsupervised)
    • Model training and evaluation
    • Overfitting and underfitting
    • Train-test split

  • Module 8: Linear Regression

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    • Simple and multiple regression
    • Regression model concepts
    • Gradient descent basics
    • Model evaluation metrics (R-squared)
    • Assumptions of linear regression

  • Module 9: Logistic Regression

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    • Classification problems
    • Logistic function and sigmoid curve
    • Model training and prediction
    • Confusion matrix
    • ROC and AUC curve

  • Module 10: Decision Trees, Random Forest & KNN

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    • Decision tree algorithm
    • Gini index and entropy
    • Random forest ensemble method
    • K-Nearest Neighbors (KNN)
    • Model comparison

  • Module 11: Clustering (K-Means)

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    • Unsupervised learning basics
    • K-Means clustering algorithm
    • Centroids and distance measures
    • Cluster evaluation techniques

  • Module 12: AI & Neural Networks

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    • Introduction to neural networks
    • Perceptron model
    • Basics of deep learning
    • Activation functions
    • Applications of AI

  • Module 13: SQL for Data Science

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    • Database concepts
    • Basic SQL queries (SELECT, WHERE, JOIN)
    • Data manipulation (INSERT, UPDATE, DELETE)
    • Using SQL with datasets

  • Module 14: Projects & Practical Training

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    • Real-world datasets handling
    • End-to-end Data Science project
    • Applying ML models to business problems
    • Model deployment basics

• High demand across industries
• Excellent salary packages
• AI-powered future career
• Work with real-world data
• Multiple career opportunities
• Global job opportunities
• Strong growth in Data & AI

• Data-driven decision making
• Customer behavior analysis
• Business forecasting
• AI & Machine Learning
• Automation
• Fraud Detection
• Business Intelligence

• Artificial Intelligence
• Generative AI
• Machine Learning
• Deep Learning
• Big Data Analytics
• Cloud Data Platforms
• Data Engineering
• Business Intelligence
• Predictive Analytics
• MLOps

• Python
• SQL
• Excel
• Statistics
• Power BI
• Tableau
• Machine Learning
• NLP
• Generative AI
• TensorFlow
• Pandas
• NumPy

• B.E./B.Tech Students
• Diploma Students
• B.Sc./BCA/MCA Graduates
• Freshers
• Working Professionals
• Software Developers
• Testing Professionals
• Anyone interested in Data Science

• Python Programming
• Data Analysis
• Data Visualization
• Machine Learning
• Deep Learning
• SQL
• Statistics
• Predictive Analytics
• Model Deployment
• AI Problem Solving

• Industry Projects
• Interview Question Bank
• Assignments
• Notes & Study Material
• Resume Building
• Certificate
• Placement Assistance

• Resume Preparation
• LinkedIn Profile Optimization
• Portfolio Review
• Mock Interviews
• Technical Interview Preparation
• HR Interview Preparation
• Job Referrals *

• IT Services
• Banking & Finance
• Healthcare
• E-Commerce
• Manufacturing
• Retail
• Telecom
• Insurance
• Consulting
• Startups
• Product Companies

Career Role Salary
Data Scientist ₹6-18 LPA
Data Analyst ₹4-12 LPA
Machine Learning Engineer ₹8-22 LPA
AI Engineer ₹8-25 LPA
Business Intelligence Developer ₹5-15 LPA
Data Engineer ₹7-20 LPA
Python Developer ₹4-12 LPA
AI Consultant ₹10-30 LPA
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Reviews

Course Content
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Your Feedback
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Smit Mahajan
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The ethical hacking and network security labs at ITKUL were amazing. The trainers guided us through real-world scenarios, and I successfully cleared my first job interview

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Rohit Verma
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The real-time projects at ITKUL made a huge difference. By the time I attended interviews, I already had hands-on experience with Java full-stack development.

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Anjali Mehta
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I joined ITKUL with zero experience in data analytics. The structured modules and real-time projects boosted my confidence, and now I’m working in a data-driven role.

Looking for the Best Data Science Training Program at the Best Software Training Institute?🚀

✅ Online & Offline Batches

✅ Weekday & Weekend Options

✅ One-Click Apply – Register easily.

✅ Live Instructor-led Sessions & Recorded Sessions

✅ Hands-On Industrial Projects & Real-world Scenarios.

✅ Practical Assignments, Regular Mock Interviews < /p>

✅ Dedicated Support Team.

✅ Placement Assistance.

✅ Course Completion Certificate

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Why Choose ITKUL

Feature Our Course
Live Interactive Sessions ✅Yes
Industry Expert Trainers ✅ Yes
Real-World Projects ✅ Yes
Placement Assistance ✅ 100% Placement Support
Hands-on Labs & Assignments ✅ Yes
1-on-1 Doubt Clearing ✅ Yes
Resume & Interview Preparation ✅ Yes
Lifetime Course Materials ✅ Yes
Final Verdict 🚀 Best Choice for Career Growth

Frequently Asked Questions

What is the duration of the Data Science course?

The duration of this course is 6 Months.

What is the fee for the Data Science course?

The course fee is ₹59999.00. The discounted fee is ₹44999.00 including training, projects, certification, and placement support.

Who can join the Data Science course?

Graduates, working professionals, and freshers interested in analytics and AI can join.

Is programming knowledge required for Data Science?

Basic programming knowledge is helpful but not mandatory. We start from fundamentals.

Which tools and technologies are covered?

Python, Statistics, Machine Learning, SQL, Data Visualization, and real-world projects.

Do you provide hands-on projects?

Yes, students work on live projects and case studies based on real industry data.

Is placement assistance provided?

Yes, we provide resume support, interview preparation, and placement assistance.

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