Data Science Training in Nepal
Turn raw data into insights and predictions with Python, statistics, SQL and ML.
- 3 Months
- Mode: Online, Hybrid & Physical Live Classes
- Beginner to Intermediate
Learn directly from Rohan Aryal
AI IntegratedTotal fee
Rs. 12,000
Start with
Rs. 6,000
Course overview
Data Science combines programming, statistics and business thinking to answer questions with data. This program trains you on the complete workflow: collecting and cleaning data, exploring it, building predictive models and communicating results clearly.
You will work with Python, SQL, Pandas, Scikit-learn and Power BI on realistic datasets from sectors like finance, retail and health. AI-assisted analysis is built into the course so you learn to work the way modern data teams do.
What you will learn
- Write clean Python for data collection and analysis
- Apply statistics and hypothesis testing to real questions
- Query and join data with SQL
- Build and evaluate predictive machine learning models
- Create dashboards and data stories for decision makers
- Use AI assistants to speed up analysis responsibly
Tools covered
Some of the major industry-relevant tools you will work with in this course:
- Python
- Jupyter
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-learn
- SQL
- PostgreSQL
- Power BI
- Streamlit
- Git
Curriculum
The complete syllabus for Data Science: every lesson, section and topic you will cover. Download it as a PDF to read offline or share it.
8 lessons · 25 sections · 78 topics
- Variables, data types and operators
- Conditions and loops
- Functions and modules
- Lists, dictionaries and comprehensions
- Reading and writing CSV, Excel and JSON
- Error handling
- Jupyter Notebook and Google Colab workflow
- Naming and structuring notebooks
- Reusable functions
- Version control with Git and GitHub
- Mean, median, mode and spread
- Percentiles and box plots
- Skewness and outliers
- Probability rules and conditional probability
- Normal, binomial and Poisson distributions
- Central limit theorem
- Sampling and confidence intervals
- Hypothesis testing and p-values
- t-tests, chi-square and ANOVA
- A/B testing for business decisions
- Correlation vs causation
- CSV, Excel, JSON and SQL sources
- Reading data from APIs
- Web scraping with requests and BeautifulSoup
- Missing values and duplicates
- Data types and string cleaning
- Merging, joining and concatenating
- Grouping and aggregation
- Pivot tables and reshaping
- Parsing dates and times
- Resampling and rolling windows
- Seasonal patterns
- Matplotlib fundamentals
- Statistical charts with Seaborn
- Interactive charts with Plotly
- Power BI: connecting and modelling data
- Building interactive Power BI reports
- Choosing the right chart for the message
- Structuring a data story
- Writing clear insights and recommendations
- Presenting to non-technical audiences
- SELECT, WHERE, ORDER BY and LIMIT
- Aggregation with GROUP BY and HAVING
- Joins across multiple tables
- Subqueries and common table expressions
- Window functions for ranking and running totals
- Date functions and CASE expressions
- Connecting Python to PostgreSQL
- Loading query results into Pandas
- Project: sales analysis with SQL
- Framing a business problem as an ML problem
- Train and test splits
- Baselines and evaluation metrics
- Linear and logistic regression
- Decision trees and random forests
- Gradient boosting
- Model evaluation and cross-validation
- K-means clustering
- Customer segmentation
- Principal component analysis
- Encoding and scaling
- Creating features from dates and text
- Feature importance and selection
- Time series components
- Moving averages and exponential smoothing
- Forecasting sales with Prophet
- Text analysis basics and sentiment
- Recommendation systems
- Using LLMs to explore and explain data
- Checking AI output for accuracy
- Building data apps with Streamlit
- Choosing a dataset and business question
- Project plan and success criteria
- End-to-end analysis and modelling
- Dashboard and written report
- Presentation to a panel
- Portfolio on GitHub
- Internship readiness evaluation
What you get
- Live instructor-led classes
- Recorded video of every session
- Hands-on projects and assignments
- 1:1 mentor support and doubt sessions
- Internship pathway after evaluation
- Verifiable completion certificate
- Learner community on Discord
- Career guidance and portfolio review
Fees & payment plan
3 Months program. Choose the class type that suits you. The curriculum, mentors, recordings and certificate are the same in every mode.
Online
Live, interactive classes over video, from anywhere in Nepal or abroad.
Rs. 12,000
Enroll online| Payment plan | Online | Hybrid | Physical |
|---|---|---|---|
First installment (50%) Payable at enrollment | Rs. 6,000 | Rs. 6,000 | Rs. 6,000 |
Second installment (50%) Payable when you are promoted to the internship | Rs. 6,000 | Rs. 6,000 | Rs. 6,000 |
| Total | Rs. 12,000 | Rs. 12,000 | Rs. 12,000 |
Your mentor
Rohan Aryal
Mentor
Rohan mentors Leafclutch Academy's AI and data programs, guiding learners from their first lines of Python to building agents, generative AI applications, machine learning models and analytics dashboards, with a strong focus on hands-on projects.
Who can join
- Basic computer skills
- Comfort with school-level mathematics
- No prior programming required
Career opportunities
- Data Scientist
- Data Analyst
- Junior ML Engineer
- Business Intelligence Analyst
Earn a high-value industry certificate
Complete Data Science and receive a certificate from Leafclutch Academy. Add it to your LinkedIn profile, resume or CV to stand out to recruiters. Every certificate carries a unique code that employers can check online.
Already earned a certificate? Verify it here
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Frequently asked questions
Is this course suitable for non-IT graduates?
Yes. Many data scientists come from commerce, science and engineering backgrounds. We start from programming basics.
Will I learn Power BI as well?
Yes. The visualization module covers Power BI dashboards alongside Python charting libraries.
What kind of projects will I do?
Sales analysis, customer segmentation, price prediction, churn prediction and a capstone on a dataset of your choice.
Start Data Science this month
Talk to our counsellors for free. We will help you choose the right course, mode and batch.