Master Data Science – Turn Data Into Decisions
AI-Ready Skills
Real-World Projects
Career Growth
Step into the most in-demand career of the decade. At D’Code Gurukul, you’ll learn Python, Statistics, Machine Learning, and Data Visualization. Build projects on real datasets and get interview-ready for top data roles.
Conquer
Data Science
120+
Hours of Live Classes
100+
Interactive Sessions
5+
Real-World Projects
Doubt Solving
+
Personal Mentorship
Resume Building
+
Interview Prep Support
Why Data Science Works for You
From Raw Data to
Career-Defining Insights
Data is the new oil. Companies need skilled professionals who can refine it into decisions.
Work With Real Data
Learn by analyzing datasets from finance, healthcare, and e-commerce — not just toy examples.
📊 Because employers want problem-solvers, not theory-memorizers.
Learn Industry Tools
Master Python, Pandas, SQL, and Power BI — the exact tools data teams use daily.
⚡ Because practical tools = career leverage.
Crack Data Interviews
From SQL queries to ML case studies — prepare with mock tests, real interview patterns, and guidance.
🔍 Because confidence comes with preparation.
Build AI-Powered Solutions
Go beyond Excel sheets — learn Machine Learning to predict, classify, and recommend.
🤖 Because future belongs to AI-ready professionals.
Unlock Global Careers
Data Science is universal. From startups to Fortune 500s, your skills will be in demand everywhere.
🌎 Because data has no borders.
Career Ready Program
Your Future - Backed by Data
Imagine presenting insights to CEOs, building predictive models, and getting hired in top companies.
Stop imagining! Start doing with D’Code Gurukul.
Curriculum Overview
The Gurukul Learning Path
Industry-focused curriculum that ensures you’re always interview and job-ready.
Python for Data Science
- Python Basics: Variables, Data Types, Loops, Functions
- File Handling & Data I/O (CSV, Excel, JSON)
- Data Structures: Lists, Dictionaries, Sets
- OOP Concepts & Best Practices
- Virtual Environments & Package Management
Numerical Computing with NumPy
- Arrays, Indexing & Slicing
- Vectorization & Broadcasting
- Mathematical Functions & Statistics
- Random Number Generation
- Performance Optimization with NumPy
Data Manipulation with Pandas
- Series & DataFrames
- Importing & Exporting Data (CSV, Excel, SQL)
- Filtering, Sorting & Aggregation
- Handling Missing Data & Outliers
- GroupBy, Merge, Join, and Pivot Tables
Databases & SQL (MySQL)
- SQL Basics: SELECT, WHERE, ORDER BY
- Joins: INNER, LEFT, RIGHT, FULL
- Aggregations & Grouping
- Subqueries & Nested Queries
- Connecting Python with MySQL
Data Analysis with Excel & Power BI
- Excel: Formulas, Pivot Tables, Data Cleaning
- Power BI Basics: Dashboards, Reports, Visualizations
- Data Import & Transformations in Power BI
- DAX Functions for Advanced Analytics
- Interactive Dashboards for Business Insights
Data Visualization (Matplotlib & Seaborn)
- Line, Bar, Scatter, Pie Charts
- Customizing Plots (Labels, Colors, Styles)
- Histograms, Boxplots & Heatmaps
- Seaborn for Statistical Visualizations
- Best Practices for Storytelling with Data
Probability & Statistics for Data Science
- Descriptive Statistics: Mean, Median, Variance
- Probability Distributions (Normal, Binomial, Poisson)
- Sampling & Hypothesis Testing
- Correlation & Regression Basics
- Confidence Intervals & p-values
Machine Learning with Scikit-learn
- Data Preprocessing & Feature Engineering
- Regression (Linear, Logistic)
- Classification Models (KNN, SVM, Decision Trees, Random Forest)
- Clustering (K-Means, Hierarchical)
- Model Evaluation: Accuracy, Precision, Recall, F1 Score
Deep Learning with TensorFlow
- Introduction to Neural Networks
- Activation Functions & Optimizers
- Building ANN with TensorFlow & Keras
- Training, Validation & Testing Models
🚀 Career-Driven Opportunities
Where Skills from
D'Code Gurukul Open Doors
























Data Power
Become the Data Professional Companies Trust
testimonial section
No Confusion - Only Clarity
Still Unsure? Let Us Clear the Path!
Explore real student doubts answered — so you can confidently step into your IT career with D’Code Gurukul.
Do I need a coding background to learn Data Science?
- Not necessarily. We start with Python basics and guide you through libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn.
What’s the difference between Data Analytics and Data Science?
- Data Analytics focuses on analyzing and visualizing past data. Data Science goes deeper — building predictive models and using Machine Learning.
Will I learn Machine Learning in this course?
- Yes, you’ll learn supervised and unsupervised ML algorithms with Scikit-Learn to build predictive models.
What kind of companies hire Data Scientists?
- Every industry — IT, finance, healthcare, retail, e-commerce, and even startups. Data is everywhere.
What projects will I work on?
- You’ll work on projects like fraud detection, recommendation systems, customer churn prediction, and sentiment analysis — projects that stand out in resumes.
Is mathematics important for Data Science?
- You’ll need to understand statistics, probability, and linear algebra. We simplify these concepts with practical examples.
What’s the starting salary of a Data Scientist?
- Freshers start around ₹3–8 LPA, and with 2–3 years of experience, salaries can go up to ₹15–20 LPA.
Do you provide placement assistance after the course?
- Yes! At D’Code Gurukul, we don’t just teach — we prepare you for real jobs. We provide 100% placement assistance through mock interviews, resume building, referrals to hiring partners, and direct job opportunities with our network of IT companies. Your success is our mission.
Do you help in building LinkedIn/GitHub portfolios?
- Definitely! A strong online presence is crucial today. We’ll guide you in building a professional LinkedIn profile and a GitHub portfolio that attracts recruiters. This is part of our Career Grooming Program to make you interview-ready.
Will you prepare me for technical interviews and HR rounds?
- Yes! We provide mock technical interviews, HR interview training, and coding challenges that replicate real hiring processes. By the time you face an actual interview, you’ll already feel like you’ve cracked 10 of them.
🚀 Your IT Career Starts Here
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IT Career Today
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