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Intermediate Track  |  Course 2

Data Science & Predictive Analytics with Python

Data analysis, visualization, ML models and real-world predictive projects.

  • 3 Months program with intermediate learning
  • Build industry-oriented projects with expert trainers
  • Certificate on completion, internship opportunity and placement guidance
  • Classroom batch at Balmatta, Mangalore, or live online

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What describes you best *

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Course Duration3 Months
Time Commitment2 Hours/day
EligibilityPursuing college / Graduate
Learning ModeOnline / Offline
Sample LPOINT certificate of completion with certificate number, QR verification and Edge Score

Why choose this course?

Data analysis, visualization, ML models and real-world predictive projects.

Expert Trainers

Learn from experienced trainers who guide you step by step, from the basics to real projects.

Industry-Oriented Projects

Build hands-on projects based on real-world use cases to apply what you learn and strengthen your portfolio.

Placement Guidance

Get help with resume building, interview preparation and job search so you are ready for the job market.

Internship Opportunity

Get an opportunity to gain practical, hands-on experience through an internship after the course.

Certificate on Completion

Receive a certificate on completing the course to showcase your skills to employers.

Face-to-Face Interview with Industry Experts

Take part in a face-to-face interview with industry experts to get feedback and build confidence for real interviews.

What you will learn

Build on your Python skills and learn how data science is done in practice. You will clean and analyse real datasets, create clear visualizations, apply statistics, and build, evaluate and improve machine learning models that predict outcomes such as sales, prices and customer behaviour. The course ends with real-world predictive projects.

Students learning together
01Data Analysis & Cleaning
  • Pandas for data manipulation
  • Handling missing values and duplicates
  • Filtering, grouping and merging data
  • Feature engineering basics
02Data Visualization
  • Matplotlib and Seaborn charts
  • Histograms, scatter and box plots
  • Correlation heatmaps
  • Telling stories with data
03Statistics for Data Science
  • Descriptive statistics
  • Probability distributions
  • Hypothesis testing
  • Correlation and regression analysis
04Machine Learning with scikit-learn
  • Linear and logistic regression
  • Decision trees and random forests
  • KNN and K-Means clustering
  • Train/test split and cross-validation
05Model Evaluation & Tuning
  • Accuracy, precision, recall and F1
  • RMSE and R-squared score
  • Overfitting and underfitting
  • Hyperparameter tuning
06Predictive Analytics in Practice
  • End-to-end predictive project workflow
  • Time-series forecasting basics
  • Saving and reusing trained models
  • Presenting results and insights

Toolkit

PythonNumPyPandasMatplotlibSSeabornscikit-learnJupyter / ColabGitHub

Industry-oriented projects

01

Customer Churn Prediction

Predict which customers are likely to leave a business using classification models.

What you will do

  1. Explore customer data and see who has left
  2. Clean the data and create useful features
  3. Train classification models and compare them
  4. Check accuracy, precision and recall, then explain the result

Skills you will use

PythonPandasClassificationModel evaluation
Project outcome

A trained churn model with a short write-up of how well it finds customers likely to leave.

02

House Price Prediction

Build a regression model that estimates property prices from real features.

What you will do

  1. Study property features such as size, location and age
  2. Engineer features and split the data for training and testing
  3. Train a regression model and tune it
  4. Measure the error with RMSE and R-squared

Skills you will use

scikit-learnRegressionRMSEFeature engineering
Project outcome

A regression model that estimates property prices, checked with RMSE and R-squared.

03

Sales Forecasting

Analyse past sales data and forecast future sales for business planning.

What you will do

  1. Load past sales and plot trends and seasonality
  2. Prepare the data as a time series
  3. Build a forecasting model for future sales
  4. Present the forecast with clear charts for planning

Skills you will use

PandasTime seriesForecastingCharts
Project outcome

A sales forecast with charts that can be used for business planning.

04

Capstone: Business Data Analysis

Capstone

Take a business dataset from raw data to insights and a predictive model, then present your results.

What you will do

  1. Choose a business dataset and define the question to answer
  2. Clean, explore and visualize the data
  3. Build and evaluate a predictive model
  4. Present your results and insights to an audience

Skills you will use

PythonData cleaningPredictive modelPresentation
Project outcome

A complete project from raw data to insights and a predictive model, presented to an audience.

Who Is This Course For?

Start your Data and AI journey with Python, Statistics, SQL and machine learning.

Degree freshers on campus Students learning together Working professional learning data skills Beginner learning at home

Take your Data and AI skills to the next level

  • Open to BCA, BSc (CS), BE / BTech, MCA, MSc (CS) and MTech students and graduates
  • Learn how data science is done in practice, using real datasets
  • Build predictive projects for your resume and portfolio
  • Get placement guidance: resume, mock interviews, aptitude and group discussion
What you gain

Hands-on data science projects and a certificate that help you stand out in campus and off-campus interviews.

Ready for the next level

  • Beginner Track students ready for the next level
  • Build on your Python, NumPy and Pandas basics
  • Learn to clean data, apply statistics and build machine learning models
  • Finish with real-world predictive projects
What you gain

A smooth step from the basics to data science and predictive modelling.

Move into data roles

  • Working professionals moving into data roles
  • Learn to clean, explore and analyse real-world data
  • Create clear visualizations and insights you can share with a team
  • Online and offline batches with 2 hours of learning per day fit around your job
What you gain

The skills to analyse data and build models that predict outcomes such as sales, prices and customer behaviour.

Build predictive models

  • Python learners who want to build predictive models
  • Knowing Python basics is a plus: variables, loops, functions and data types
  • Basic NumPy, Pandas, maths and statistics are helpful
  • New to Python? Start with Course 1: Python for Data Science & Machine Learning
What you gain

The ability to build, evaluate and improve machine learning models on real data.

Placement guidance

Prepare to take your skills into the job market through:

Resume GuidanceProject PresentationTechnical Interview PreparationMock InterviewsAptitudeHR RoundTechnical RoundGroup DiscussionLinkedIn GuidanceJob Search Guidance

Frequently asked questions

Do I need to know Python before joining?

Knowing Python basics is a plus: variables, loops, functions and data types, along with basic NumPy and Pandas. If you are new to Python, start with Course 1: Python for Data Science & Machine Learning.

Who can join this course?

Degree freshers (BCA, BSc CS, BE/BTech, MCA, MSc CS, MTech), Beginner Track students ready for the next level, working professionals moving into data roles, and Python learners who want to build predictive models.

How long is the course?

Three months, planned as a 12-week roadmap from data analysis and visualization to real-world predictive projects.

What projects will I build?

Customer churn prediction, house price prediction, sales forecasting and a capstone business data analysis project.

Will I get a certificate?

Yes. You receive a certificate on completion, and an internship opportunity is part of the program.

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Finished a course? Put it to work in our AI internship in Mangalore, or see all AI courses in Mangalore.

Contact Us

Visit us at 6th Level, Oberle Towers, Balmatta, Opp. Juice Junction, Mangalore, Karnataka 575001 · +91 78925 81597 · (0824) 4256456

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