45-Day Data Science Internship Program
Learn Data Science with a guided 45-day job-focused plan
Python | NumPy | Pandas | SQL | Power BI / Tableau
Visualization | Machine Learning | Projects | Interview Support
Built for learners who want structure, hands-on practice and a faster transition into analytics and data science roles.
Offline Jaipur + online support
Beginner-friendly path
Live projects and assignments
Join Seldom India for a compact training journey covering Python, data handling, SQL, visualization, exploratory analysis and machine learning basics. The focus stays on practical learning, guided project work and job-readiness support.
- Live practical sessions with trainer guidance and regular doubt support
- Portfolio-ready mini projects, resume refinement and interview preparation
- Certificate, recorded learning support and structured practice tasks
45 DaysFocused learning schedule with guided progression from basics to project work.
687+Google reviews on Seldom India profile, showing visible learner trust.
2014Training experience since, with classroom-led support in Jaipur.
AI
Quick Enquiry
Get fees and batch timing
Share your details and our team will connect with the most suitable batch option for you.
Best fit forStudents, graduates, working professionals and beginners who want structured guidance.
What you leave withProjects, confidence with tools, portfolio material and clearer interview answers.
About the Program
Kickstart your career in Data Science with a faster, focused curriculum built to make practical learning easier to follow.
This 45-day program is structured for learners who want guided training in Python, data handling, SQL, visualization and machine learning basics without getting lost in scattered content. You work on real datasets, build guided projects and learn how to explain your work with confidence.
Why Choose Us?
Beginner FriendlyStart coding even if you have zero prior knowledge.
Practical LearningLearn by doing real-world tasks and projects.
Job OrientedBuild skills that help you become job ready.
Guided SupportGet trainer and mentor help at every step.
Program Highlights
The flow is built to help you move from basics into analysis, projects and presentation-ready outcomes instead of just covering theory topic by topic.
Live interactive sessionsReal-time learning with guided explanation and doubt support.
Certificate of completionGet recognized after completing the full training program.
Real-world projectsPractice with datasets, dashboards and model-building tasks.
Placement assistanceSupport for interviews, resume and job-readiness preparation.
Hands-on coding practiceRegular practice across Python, SQL and analysis workflows.
Resume and interview prepStructure your profile around projects and practical learning.
Mentorship supportClear guidance while learning and building confidence.
Job-ready in 45 daysA focused plan for skill-building in a compact timeline.
45-Day Course Outline: Days 1 to 15
| Day | Topics to be Covered | Practical / Project |
|---|---|---|
| 01Day | Introduction to Data Science, use cases, applications and career opportunities | Understand the data science landscape |
| 02Day | Python basics, installation, setup, first program and input | Write your first Python program |
| 03Day | Variables, data types, type casting and working with values | Practice basic data types |
| 04Day | Operators: arithmetic, comparison, logical and assignment operations | Solve operator-based problems |
| 05Day | Conditional statements: if, elif, else and nested conditions | Build a simple decision program |
| 06Day | Loops in Python: for, while, nested loops | Pattern programs |
| 07Day | Lists: create, access, update, delete and list methods | Student list management |
| 08Day | Tuples and tuple methods | Store immutable data |
| 09Day | Sets and set operations | Remove duplicates |
| 10Day | Dictionaries, keys, values and methods | Create dictionary-based apps |
| 11Day | Functions: parameters, return values and scope | Build reusable functions |
| 12Day | File handling: read, write, append and file modes | Notes manager application |
| 13Day | NumPy basics, arrays and operations | Work with arrays |
| 14Day | NumPy indexing, slicing and mathematical operations | Array calculations |
| 15Day | Mini Project 1: calculator or to-do application | Complete mini project |
45-Day Course Outline: Days 16 to 30
| Day | Topics to be Covered | Practical / Project |
|---|---|---|
| 16Day | Pandas basics: Series, DataFrame and creating structures | Create your first DataFrame |
| 17Day | Data loading from CSV, Excel and TXT | Load and explore datasets |
| 18Day | Data cleaning 1: handling missing values, drop, fill and replace | Clean missing data |
| 19Day | Data cleaning 2: duplicates and type conversion | Clean messy datasets |
| 20Day | Data analysis with Pandas: filtering, sorting, grouping and aggregation | Summary reports from data |
| 21Day | EDA univariate analysis: mean, median, mode and distributions | Analyze single features |
| 22Day | EDA bivariate analysis and correlation | Find relationships in data |
| 23Day | Matplotlib basics: line plot, scatter plot, bar plot and histogram | Create basic charts |
| 24Day | Seaborn visualizations: countplot, boxplot, pairplot and heatmap | Advanced visualizations |
| 25Day | Data visualization project and dashboard storytelling | Generate insight report |
| 26Day | Feature engineering 1: handling outliers and binning | Prepare data for ML |
| 27Day | Feature engineering 2: label encoding and one-hot encoding | Encode categorical data |
| 28Day | Feature scaling: standard scaler and min-max scaler | Scale numerical features |
| 29Day | Train test split and data preparation for modeling | Split dataset |
| 30Day | Mini Project 2: data cleaning and EDA project | Complete analysis project |
45-Day Course Outline: Days 31 to 45
| Day | Topics to be Covered | Practical / Project |
|---|---|---|
| 31Day | Introduction to Machine Learning and types of ML | Understand ML concepts |
| 32Day | Linear regression, simple and cost function basics | Build linear regression model |
| 33Day | Multiple linear regression and feature building | Predict using multiple features |
| 34Day | Logistic regression and binary classification | Build logistic regression model |
| 35Day | Model evaluation metrics: accuracy, precision, recall, F1 and confusion matrix | Evaluate ML models |
| 36Day | Hyperparameter tuning, grid search and cross validation | Improve model performance |
| 37Day | SQL basics: introduction, tables and databases | Create database structure |
| 38Day | SQL queries: SELECT, WHERE, ORDER BY, LIMIT and DISTINCT | Write basic queries |
| 39Day | SQL joins: inner, left, right and full join | Combine multiple tables |
| 40Day | SQL aggregations: GROUP BY, HAVING and aggregate functions | Generate summary reports |
| 41Day | Final project planning and problem statement | Finalize project idea |
| 42Day | Final project analysis, data cleaning and EDA | Analyze and visualize data |
| 43Day | Final project model building and evaluation | Build and test model |
| 44Day | Dashboard and report creation using Power BI / Tableau / Streamlit | Build interactive dashboard |
| 45Day | Final presentation and career guidance | Final presentation and feedback |
Projects You Will Build
Sales Data AnalysisClean, analyze and visualize sales data.
HR Analytics DashboardEmployee insights and analytics reporting.
Prediction ModelBuild an ML model for a real-world prediction use case.
End-to-End Data Science ProjectComplete project from data to deployment-ready output.
Career Outcomes
Data AnalystReporting, dashboarding and business insights.
Business AnalystDecision support through data-driven thinking.
Junior Data ScientistData preparation, ML basics and model support.
Data EngineerStructured data handling and workflow foundations.
Start your data science journey today
Learn faster with a focused 45-day plan
Limited seats available
Hands-on learning
100% practical training
Job-ready in 45 days
AI