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KenStack Data Science Course Syllabus (Phase-wise)
This Data Science course is designed for students and professionals to master the complete data science lifecycle — from data collection, preparation, analysis, and visualization to predictive modeling and deployment. Includes hands-on projects and case studies.

Phase 1: Foundations of Programming & Analytics

1. Python Programming for Data Science

Objectives:

• Learn Python essentials for analysis & ML.

Topics:

• Variables, Data Types, Operators
• Lists, Tuples, Dictionaries, Sets
• Conditions, Loops, Functions
• Modules, File Handling
• OOP Basics, Exception Handling

2. Statistics & Probability

Topics:

• Data Types & Sampling
• Mean, Median, Mode
• Variance, Std. Deviation
• Bayes Theorem, Probability
• Distributions (Normal, Binomial, Poisson)
• Hypothesis Testing (t-test, z-test, Chi-square)

3. Excel for Data Analysis

• VLOOKUP, IF, COUNTIF
• Pivot Tables & Charts
• Dashboards & Data Cleaning

Phase 2: Data Analysis & Visualization

4. Data Analysis with Python

• Numpy, Pandas
• Handling Missing Values
• Merging, Joining, Grouping

5. Data Visualization with Python

• Matplotlib
• Seaborn
• Plot Customization
• Plotly (optional)

6. SQL for Data Science

• SELECT, WHERE, GROUP BY
• JOINS, Subqueries
• Table Creation
• Real SQL Projects

Phase 3: Machine Learning & Predictive Modeling

7. Introduction to Machine Learning

• Supervised vs Unsupervised Learning
• ML Pipeline & Lifecycle
• Train/Test, Cross Validation

8. Supervised Algorithms

• Linear & Logistic Regression
• Decision Tree, Random Forest
• KNN, SVM

9. Unsupervised Algorithms

• K-Means Clustering
• Hierarchical Clustering
• PCA – Dimensionality Reduction

10. Model Evaluation & Tuning

• Accuracy, Precision, Recall
• AUC-ROC
• Grid Search & Random Search

Phase 4: Project & Deployment

11. Real-Time Projects

• Sales Prediction
• Customer Segmentation
• Employee Attrition
• E-commerce Dashboard

12. Deployment Basics

• Flask/Streamlit intro
• Hosting a Model
• GitHub Version Control

KenStack Data Analytics Course Syllabus (Phase-wise)
This Data Analytics course equips students and professionals with practical data analysis skills using industry-standard tools such as Excel, SQL, Python, and data visualization platforms. Includes hands-on assignments, use-case driven practice, and real-world projects.

Phase 1: Data Fundamentals & Excel Mastery

1. Microsoft Excel for Data Analysis

Objectives:

• Build strong foundations in spreadsheet-based data analytics.
• Learn to clean, analyze, and visualize data.

Topics Covered:

• Basic & Advanced Excel Functions
• Data Sorting, Filtering, and Cleaning
• Pivot Tables, Charts & Dashboards
• Conditional Formatting
• What-If Analysis and Goal Seek

Phase 2: SQL for Data Manipulation

2. SQL (Structured Query Language)

Objectives:

• Learn to retrieve and manipulate structured data from databases.

Topics Covered:

• Basics: SELECT, WHERE, ORDER BY, GROUP BY, HAVING
• JOINs: INNER, LEFT, RIGHT, FULL
• Subqueries, Aggregate Functions (COUNT, SUM, AVG, etc.)
• Table Creation, Insertion, Updates, and Deletion
• Real-time practice on large datasets

Phase 3: Data Analysis with Python

3. Python Programming for Analytics

Objectives:

• Analyze data using Python libraries.
• Perform data cleaning, wrangling, and transformation.

Topics Covered:

• Python Basics: Data Types, Conditions, Loops, Functions
• NumPy for Numerical Computation
• Pandas for Data Manipulation
• Handling Missing Data, Filtering, Sorting, Grouping
• Working with Excel, CSV, and SQL files in Python

4. Data Visualization with Python

Objectives:

• Create insightful and meaningful charts using Python.

Topics Covered:

• Matplotlib: Bar, Line, Pie, Histogram
• Seaborn: Box Plot, Heatmap, Distribution Plots
• Basic Dashboard Creation (Optional)

Phase 4: Business Insights & Reporting

5. Data Storytelling & Business Analytics Concepts

Objectives:

• Derive meaningful insights from data.
• Present data to support business decisions.

Topics Covered:

• KPI Analysis, Trend Analysis
• Correlation & Pattern Identification
• Real-life Business Use Cases
• Effective Reporting Techniques

6. Power BI / Tableau (Optional Based on Track Chosen)

Objectives:

• Learn to build interactive dashboards for business users.

Topics Covered:

• Data Importing, Cleaning
• Visualizations: Bar, Line, Map, KPI
• Filters, Slicers, Drill-downs
• Publishing Reports

Final Phase: Projects & Tools

7. Tools Covered

• Microsoft Excel
• MySQL / PostgreSQL
• Python (Pandas, NumPy, Matplotlib, Seaborn)
• Power BI or Tableau (optional)
• Jupyter Notebook / VS Code

8. Capstone Projects

Sample Projects:

• Sales Performance Dashboard
• Customer Behavior Analysis
• HR Analytics (Attrition/Performance)
• Marketing Campaign Analysis

KenStack Full Stack Course Syllabus (Phase-wise)
This Full Stack course equips students with skills to build complete web applications, from frontend to backend, using industry-standard technologies and frameworks. Includes hands-on assignments and real-world projects.

Phase 1: Frontend Development

1. HTML5 – HyperText Markup Language

Objectives:

• Build strong HTML fundamentals.
• Create structured and semantic web pages.

Topics Covered:

• HTML Basics, Elements, Attributes, Headings, Paragraphs, Formatting
• HTML Lists, Tables, Forms, Links, Images
• Semantic HTML5 Tags
• HTML Layouts, Classes, IDs
• HTML Responsive Design
• Embedding iFrames, JavaScript
• HTML with CSS Integration

2. CSS3 – Cascading Style Sheets

Objectives:

• Design responsive and attractive web pages.
• Implement layouts using modern CSS techniques.

Topics Covered:

• CSS Syntax, Selectors, Box Model
• Backgrounds, Borders, Padding, Margin
• CSS Positions, Float, Display
• Text and Font Styling, Links, Lists, Tables
• Pseudo-classes & Pseudo-elements
• Media Queries, CSS Grid & Flexbox
• Animations, Transforms (2D & 3D)

3. Tailwind CSS

Objectives:

• Learn utility-first CSS framework.
• Build custom UIs rapidly using Tailwind.

Topics Covered:

• Introduction to Tailwind
• Installation and Configuration
• Utility Classes (Layout, Spacing, Typography, Borders)
• Responsive Design with Tailwind
• Component-based Styling (Navbar, Cards, Forms, Buttons)
• Using Tailwind with JS Frameworks (like React)

4. Bootstrap

Objectives:

• Use Bootstrap to speed up UI development.
• Understand grid systems and responsive design.

Topics Covered:

• Bootstrap Basics, Grids, Components
• Buttons, Forms, Modals, Carousels
• Bootstrap Utilities & JavaScript Plugins

5. JavaScript

Objectives:

• Master JavaScript fundamentals for interactivity.
• DOM manipulation, event handling, and logic building.

Topics Covered:

• Basics: Variables, Loops, Conditions, Functions
• Arrays, Objects, Events, Strings, Numbers
• Form Validation, Error Handling
• JavaScript DOM & BOM
• Advanced: Closures, Hoisting, Strict Mode, Debugging

Phase 2: Frontend Frameworks & Dynamic Development

6. ReactJS

Objectives:

• Build single-page applications using reusable components.
• Understand state management and routing.

Topics Covered:

• JSX, Components, Props, State
• Component Lifecycle, Hooks (optional)
• Forms, Lists & Keys
• Routing, Redux Basics
• Integrating APIs & AJAX
• Project: Build a UI with React

Phase 3: Backend Development & Integration

7. PHP & MySQL

Objectives:

• Learn dynamic backend development.
• Connect web forms with databases.

Topics Covered:

• PHP Syntax, Forms, Sessions, Cookies
• Working with Files
• PHP MySQL Database CRUD Operations
• Exception Handling
• Connecting PHP with SQL Server and phpMyAdmin

8. Laravel (PHP Framework)

Objectives:

• Build scalable web apps with MVC architecture.
• Implement authentication and APIs.

Topics Covered:

• Laravel Setup, Blade Templating
• Routing & Controllers
• Migrations & Database Integration
• Authentication System
• Eloquent ORM, Admin Panel
• Ajax, jQuery, Composer Packages
• Security & Session Management

9. Testing & Project Deployment

Objectives:

• Understand basic testing principles.
• Learn how to host and deploy web apps.

Topics Covered:

• Manual Testing of Modules
• Local Hosting
• Live Deployment on Hosting Platforms (optional)
• Git & GitHub Version Control (optional)

Tools & Final Project

• VS Code, Chrome DevTools, Postman, Git, XAMPP
• Capstone Project: Build a Full Stack Web Application (Frontend + Backend + Database)