Learn data science through hands-on training with real datasets and practical projects. Build strong analytical skills, perform data visualization, and develop machine learning models while gaining experience in SQL, statistics, and business intelligence tools within 3 months.
Flexible learning, online or offline
Training with US-based company exposure
Assessment-based NASSCOM certification
Curriculum designed for real job roles
This 3-month program focuses on building strong data science skills through a structured and practical approach. You will learn Python, statistics, data analysis, machine learning, and visualization while working on real datasets and industry-oriented projects.
This course is ideal for students and professionals aiming to build a career in data science and analytics. Students should have a good understanding of mathematics and be comfortable with Python programming, including data manipulation using libraries like NumPy and Pandas.
Certification will be awarded based on performance in assessments and project evaluations. Learners who successfully meet the required criteria will receive a certificate affiliated with NASSCOM, validating their data science skills.
Learn Python programming, data structures, and statistical concepts like probability, distributions, and sampling techniques.
Work with Pandas, clean datasets, handle missing values, detect outliers, and prepare data for analysis.
Use SQL queries, joins, aggregations, and advanced functions to extract and analyze structured data efficiently.
Use SQL queries, joins, aggregations, and advanced functions to extract and analyze structured data efficiently.
Apply ensemble methods, clustering, dimensionality reduction, and basic feature engineering for improved model performance.
Create dashboards using BI tools and deploy models using Streamlit with basic API integration.


































































At Skill Se Safalta, we help every learner become confident, capable, and ready for real-world career opportunities.
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