Data Science Training

Become a Certified Data Scientist with Sankalpa Skills and master Python, Machine Learning, Data Analysis, Data Visualization, SQL, and AI concepts. Gain hands-on experience with real-world projects and accelerate your career in the data-driven industry.

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Explore Our Industry-Aligned Curriculum

Introduction to Data Science & Python

Introduction to Data Science
Understand the fundamentals of data science, including its applications, lifecycle, and importance in decision-making. Learn how data-driven approaches help businesses solve problems, improve efficiency, and gain competitive advantages across industries.
Python for Data Science
Learn Python programming basics including variables, data types, loops, and functions. Python is widely used in data science for analysis, automation, and building machine learning models.
Working with Jupyter Notebook
Get hands-on experience using Jupyter Notebook for writing and executing Python code. Learn how to document, visualize, and share your data science workflows effectively.
Data Structures in Python
Understand lists, tuples, dictionaries, and sets. Learn how to manipulate and store data efficiently for analysis tasks

Data Visualization

Introduction to Data Visualization
Understand the importance of visualizing data for better insights and decision-making.
Matplotlib & Seaborn
Create charts, graphs, and visualizations using Matplotlib and Seaborn libraries.
Advanced Visualization Techniques
Build interactive and advanced charts to represent complex datasets clearly.
Dashboard Creation
Create dashboards using tools like Power BI or Tableau for data storytelling

Statistics for Data Science

Descriptive Statistics
Learn measures like mean, median, mode, and standard deviation to summarize data.
Probability Basics
Understand probability concepts and their role in data analysis and predictions.
Inferential Statistics
Draw conclusions from data using sampling, confidence intervals, and hypothesis testing.
Statistical Distributions
Study normal distribution, binomial distribution, and other important statistical models

Machine Learning Fundamentals

Introduction to Machine Learning
Understand supervised and unsupervised learning concepts and their real-world applications.
Regression Algorithms
Learn linear and logistic regression techniques for prediction and classification tasks.
Classification Algorithms
Use algorithms like decision trees and KNN for classification problems.
Model Evaluation Techniques
Evaluate models using accuracy, precision, recall, and confusion matrix

Data Analysis with NumPy & Pandas

Introduction to NumPy
Learn NumPy for numerical computing. Perform operations on arrays, matrices, and large datasets efficiently.
Pandas for Data Analysis
Use Pandas to load, clean, and manipulate structured data. Work with DataFrames for real-world datasets.
Data Cleaning & Preprocessing
Handle missing values, duplicates, and inconsistent data. Prepare clean datasets for accurate analysis.
Exploratory Data Analysis (EDA)
Analyze datasets using statistical methods and visualizations to identify patterns, trends, and insights.

Advanced Machine Learning

Ensemble Methods
Learn advanced models like Random Forest and Gradient Boosting for better accuracy.
Support Vector Machines (SVM)
Understand SVM for classification and regression tasks.
Feature Engineering
Create and select important features to improve model performance.
Hyperparameter Tuning
Optimize models using techniques like Grid Search and Random Search.

Deep Learning

Introduction to Deep Learning
Understand neural networks and deep learning fundamentals.
Artificial Neural Networks (ANN)
Learn how ANN works for prediction and classification tasks.
Convolutional Neural Networks (CNN)
Use CNN for image processing and computer vision applications.
Recurrent Neural Networks (RNN)
Work with sequential data using RNN for tasks like time-series prediction.

Natural Language Processing (NLP)

Introduction to NLP
Understand how machines process and analyze human language.
Text Preprocessing
Clean and prepare text data using tokenization, stemming, and lemmatization.
Sentiment Analysis
Analyze opinions and sentiments from text data.
Text Classification
Build models to classify text into categories

Big Data & Tools

Introduction to Big Data
Understand big data concepts and tools used for large-scale data processing.
Hadoop & Spark Basics
Learn distributed computing using Hadoop and Apache Spark.
Data Warehousing
Understand how data is stored and managed in warehouses.
ETL Processes
Learn Extract, Transform, Load processes for data integration.

Projects & Career Preparation

End-to-End Data Science Project
Work on real-world projects covering data collection, analysis, modeling, and deployment.
Model Deployment
Deploy machine learning models using Flask or cloud platforms.
Resume Building & Portfolio
Create a strong portfolio showcasing projects and skills.
Interview Preparation
Prepare for data science interviews with common questions and case studies.

Get Industry-Ready with Comprehensive Career Support

How our program works

Enhance Your Skills to Transform Your Career Path

Gain official proof of your expertise from a trusted institution, increasing your value in the eyes of employers and clients.
Stand out in competitive job markets and unlock better job roles, promotions, or freelance opportunities.
Certifications ensure your skills are aligned with current industry standards, making you job-ready from day one.
Completing a certified course strengthens your belief in your capabilities and readiness to tackle real-world challenges.
Join a professional community, gain access to hiring managers, and receive support from placement partners and mentors.

Build a Job-worthy Project-Portfolio

Gain hands-on experience with cutting-edge cloud services that will equip you with the essential skills needed to thrive in a cloud computing career

Land Your Dream Job Our Alumni

Frequently Asked Questions (FAQ)

Who can join your courses?

Anyone from students to working professionals can join. Beginner courses require no prior experience.

Are your classes online or offline?

We offer both online live classes and offline classroom sessions.

Do you provide placement assistance?

Yes, our placement team assists with resume building, interviews, and connecting students to IT companies.

Are course materials provided?

Yes, students receive study materials, assignments, and project-based exercises

Do you provide soft skills or interview preparation?

Yes, we provide resume building, mock interviews, and soft skills training.

Are there weekend-only batches?

Yes, we offer weekend batches for students and professionals with tight schedules.

Are the classes live or recorded?

We offer a mix of live sessions and pre-recorded content for flexible learning.

What is Sankalpa Infotech?

Sankalpa is a leading software training institute that provides high-quality training in IT, development, cloud computing, cybersecurity, and more.

What are the class timings?

We provide flexible class timings including weekdays and weekends to suit working professionals and students.

Can I get a demo class before enrolling?

Yes, we offer free demo sessions so you can experience the quality of our training before enrolling.

What are the prerequisites to join?

Most beginner-level courses have no prerequisites. Advanced programs may require basic IT or coding knowledge

What makes Sankalpa different from others?

We focus on practical learning, expert trainers, flexible schedules, placement support, and industry-ready curriculum.

What Our Learners Have To Say

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Our programs combine real-world projects, expert mentorship, and globally recognized certifications. empowering you to launch and grow your career in the cloud and beyond