Data Science with Python Begineer
Complete data science foundation with Python, statistics, and data analysis.
Sashank Mishra
Python Backend Developer
Overview
Learn the complete data science workflow — Python programming, statistics, data wrangling, visualization, and storytelling with data.
Skills You'll Learn
Prerequisites
- No prior experience needed
Course Roadmap
Module 1
Modules 1–3: Python for Data Science → Statistics for Data Science
The daily toolkit of a data scientist. Communicate findings clearly. The statistical foundation behind every insight.
Module 2
Modules 4–6: Exploratory Data Analysis → Feature Engineering
Understand a dataset before modeling it. Bridge from analysis to prediction. Where good data science pays off.
Module 3
Modules 7–9: SQL for Data Scientists → Time Series Basics
Pull your own data from real databases. Make data-driven product decisions. Work with data that changes over time.
Module 4
Modules 10–12: Data Storytelling & Dashboards → Capstone Project
Turn analysis into decisions. Handle data the way it really shows up. Your complete data science portfolio piece.
Course Curriculum
12 modules · 9 quizzes
- NumPy & Pandas deep dive
- Data cleaning workflows
- Jupyter workflow best practices
- Matplotlib & Seaborn
- Plotly for interactive charts
- Storytelling with data
- Descriptive statistics
- Probability distributions
- Hypothesis testing
- EDA workflow
- Outlier detection
- Correlation analysis
- Regression & classification basics
- Train/test methodology
- Model evaluation
- Encoding & scaling
- Handling missing data
- Creating meaningful features
- Querying data for analysis
- Joins & aggregations
- Connecting SQL to Python
- Designing an experiment
- Statistical significance
- Common pitfalls
- Trend & seasonality
- Simple forecasting models
- Evaluating forecasts
- Building a dashboard
- Presenting to non-technical stakeholders
- Structuring a data report
- Messy data challenges
- Data pipelines basics
- Reproducible analysis
- End-to-end analysis project
- Model + insights + presentation
- Portfolio polish
Projects
Exploratory Data Analysis Report
A full EDA report on a real-world dataset with actionable insights.
Sales Forecasting Model
A simple time-series forecast for a retail dataset.
A/B Test Analysis
Analyze a real A/B test dataset and report significance.
Interactive Dashboard
A Plotly/Dash dashboard summarizing a dataset for stakeholders.
Assignments
Pandas Data Cleaning Drill
Easy10 real-world data cleaning exercises.
EDA on a New Dataset
EasyPerform and document a full EDA on an unseen dataset.
Hypothesis Testing Exercise
MediumRun and interpret 3 hypothesis tests.
SQL Query Practice
Medium10 analytical SQL queries against a sample database.
Build a Simple Forecast
HardForecast next-month values for a time series dataset.
Design an A/B Test
HardPlan a full experiment: hypothesis, metric, sample size.
Meet Your Instructor
Sashank Mishra
Python Backend Developer
1+ Years of Experience python backend, Flask, Django, MongoDB, SQLite etc.
Certificate You'll Earn
CERTIFICATE ID: LNTRN-UPSK-000000
Your Name Here
Successfully completed the Data Science Certificate at Lunetron Web Services. We appreciate their dedication and wish them success in their career.”
ISSUING DATE - 27TH MARCH, 2026
Certified data science professional.
Student Reviews
The Machine Learning and Deep Learning courses are incredibly well structured. The instructors explain complex concepts simply, and the capstone project became the centerpiece of my portfolio.
Aarush Rai
B.Tech / AI-ML
I liked the hands-on approach of the training. Working on assignments and mini projects made the concepts easier to understand, and the AI/ML introduction was a useful addition to the course.
Divyanshu Mishra
B.Tech / AI-ML
The Machine Learning and Deep Learning courses are incredibly well structured. The instructors explain complex concepts simply, and the capstone project became the centerpiece of my portfolio.
V K Srivarshini
B.Tech / CSE
₹9,999
₹19,999
50% off · Save ₹10,000
Career Outcomes
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