Become Job-Ready in Data Science, Python & Machine Learning
Build Python, SQL and ML projects that you can explain in interviews, with placement preparation from resume to mock interviews.
Roles students can target
These entry-level roles connect the course skills to real interview opportunities.
Data Scientist
Machine Learning Engineer
Python Data Analyst
AI/ML Associate
BI Analyst
Junior Data Engineer
What you'll use in every class
Industry tools covered in training, projects, and placement preparation.
Learn the skills companies ask in interviews
Each module builds toward projects, resume confidence, and interview answers.
Python Programming for Data Science
- Python syntax, variables, data types, operators, and control flow
- Functions, modules, packages, virtual environments, and pip
- OOP in Python — classes, inheritance, dunder methods, and decorators
- List comprehensions, generators, lambda, map, filter, and itertools
- File handling — reading CSV, JSON, and Excel for data loading
- Jupyter Notebook — running experiments, markdown, and sharing findings
Statistics & Probability for Data Analysis
- Descriptive statistics — mean, median, mode, variance, standard deviation
- Probability basics — distributions, Bayes theorem, and Central Limit Theorem
- Hypothesis testing — t-test, chi-square test, ANOVA, and p-value interpretation
- Correlation and covariance — understanding feature relationships
- Outlier detection and handling skewed or imbalanced data distributions
SQL for Data Scientists
- SELECT queries — filtering, ordering, grouping, and aggregate functions
- Joins — INNER, LEFT, RIGHT, FULL OUTER with real business datasets
- Subqueries, CTEs, and window functions — ROW_NUMBER, RANK, LAG, LEAD
- Data cleaning in SQL — handling NULLs, deduplication, and type casting
- Connecting MySQL to Python — feeding query results into Pandas DataFrames
Data Wrangling with Pandas & NumPy
- NumPy arrays — vectorized operations, broadcasting, and matrix arithmetic
- Pandas Series and DataFrames — loading, indexing, slicing, and filtering
- Data cleaning — handling missing values, duplicates, and inconsistent formats
- Merging, grouping, pivoting, and reshaping datasets for analysis
- Time series data — resampling, rolling windows, and date-based operations
Data Visualization & Exploratory Data Analysis
- Matplotlib — line, bar, scatter, histogram, subplots, and chart customization
- Seaborn — heatmaps, boxplots, pairplots, and statistical chart defaults
- Plotly — interactive charts and dashboards inside Jupyter Notebook
- EDA workflow — identifying patterns, outliers, correlations, and business questions
- Storytelling with data — presenting insights clearly to non-technical stakeholders
Machine Learning Algorithms & Projects
- Supervised learning — Linear Regression, Logistic Regression, Decision Trees
- Ensemble methods — Random Forest, Gradient Boosting, XGBoost
- Model evaluation — accuracy, precision, recall, F1-score, confusion matrix, ROC-AUC
- Feature engineering, selection, and hyperparameter tuning with GridSearchCV
- Unsupervised learning — K-Means clustering, PCA for dimensionality reduction
- Model saving with Pickle/Joblib and serving predictions via a Flask endpoint
Projects students can show during interviews
Telecom Subscriber Churn Prediction
Classification model on telecom data — specific domain makes it stand out in interviews.
Retail Store Weekly Demand Forecast
Time-series regression — useful for explaining prediction and trend analysis.
Bank Loan Default Risk Analysis
Finance domain classification — precision/recall focus shows ML evaluation depth.
Hospital Patient Readmission Likelihood Model
Healthcare ML — healthcare domain projects get immediate attention in interviews.
25,000+ students placed — here's a few
These are actual placements from The Kiran Academy — verified and updated regularly.
Our students are working at
Watch mock interviews & practice sessions
See how real interviews go — preparation, answers, and feedback included.
What Is AI & Data Science? | Explained for Beginners
Crack Your First Python Interview | Data Science & SQL
Python Interview for Freshers | Core Python Mock Interview
9-Year-Old Python Genius — Are You Keeping Up?
One Interview Can Change Your Entire Career!
Make Your Resume Perfect with ChatGPT — Get Shortlisted!
What Is AI & Data Science? | Explained for Beginners
Crack Your First Python Interview | Data Science & SQL
Python Interview for Freshers | Core Python Mock Interview
9-Year-Old Python Genius — Are You Keeping Up?
One Interview Can Change Your Entire Career!
Make Your Resume Perfect with ChatGPT — Get Shortlisted!
What our placed students say
From basics to placement preparation
Python + SQL Foundation
Start from practical coding, queries, and data handling.
Analytics + Visualization
Clean data, explore patterns, and create reports.
Machine Learning Projects
Build models, evaluate them, and improve predictions.
Portfolio + Placement Prep
Resume, mock interviews, GitHub and project explanation.
Good fit for these students
- BCA, BCS, BE, BTech, BSc, MCA, MBA students
- Freshers who want data jobs
- Working professionals moving into AI/ML
- Non-IT students ready to learn Python
Beginner career path
Your first class is free.
Attend a demo session before you decide. No obligation, no fees — just learning.
Data Science or Data Analytics?
Choose Data Science if you want Python, machine learning, prediction models, and AI-related roles.
Common student doubts
Short answers for course, placement, and project expectations.
Yes. The course starts from Python basics with zero assumed knowledge, then progresses into statistics, SQL, data analysis, and machine learning. Students from BSc, commerce, and non-IT backgrounds have successfully completed the course and got placed.
A fresher data scientist or ML engineer in Pune typically earns between ₹4 LPA and ₹6 LPA. With 1–2 years of experience and a strong project portfolio, salaries range from ₹6 LPA to ₹9 LPA. Product companies and AI-focused startups in Pune can pay ₹8–12 LPA for mid-level professionals.
Yes. Data science and machine learning are among the fastest-growing job categories in India. Companies across banking, telecom, healthcare, e-commerce, and IT services are actively hiring. Freshers with Python, SQL, Pandas, and at least 2 portfolio ML projects get shortlisted regularly. Hands-on project skills matter more than theory alone.
Data Analytics focuses on interpreting existing data using Excel, SQL, and Power BI to answer business questions and build dashboards. Data Science goes further — it involves building predictive models using Python, machine learning algorithms, and statistics to forecast outcomes and automate decisions. Choose Data Analytics for reporting roles; choose Data Science for ML and AI-related jobs.
Yes. You will build 4 portfolio-ready ML projects — telecom churn prediction, demand forecasting, loan default risk analysis, and hospital patient readmission model — across different domains so you can explain them confidently in any interview.
Major companies hiring data scientists and ML engineers in Pune include TCS, Infosys, Persistent, Capgemini, Accenture, Mphasis, Zensar, ThoughtWorks, and various fintech and healthtech startups. Freshers from The Kiran Academy have been placed at Capgemini, Infosys, Persistent, and several mid-size product companies.
Yes. Placement support includes resume preparation built around your ML projects, mock interviews for Python, SQL, statistics, and model explanation, GitHub portfolio setup, and dedicated placement calls with interview question preparation.
Most students who complete the course with projects start getting interview calls within 30–60 days of finishing the placement preparation module. Placement timelines vary based on how actively you apply and how well your projects are explained.
Any graduation degree is acceptable — BCA, BSc, BTech, BE, MCA, MBA, or a commerce background. The course starts from Python basics with zero assumed knowledge.
Yes. A laptop with at least 8GB RAM is recommended. All software — Anaconda, Jupyter, Python, VS Code — is free to install. No paid tools are required.
Batches are kept small (max 12 students) to ensure individual attention. Both weekday and weekend batches are available. Contact us at +91 8888809416 for the current schedule.
Yes. You will receive a course completion certificate from The Kiran Academy along with your project portfolio hosted on GitHub — which is typically more valuable than a certificate during technical interviews.
