Advance Diploma in Artificial Intelligence & Machine Learning
( A Placement Oriented Program )
Transform Data into Intelligence. Shape the Future with AI.
100 % Placement Opportunities with
| Hands-On Projects Industry | Recognised Certification
Eligibility: BE, B.Tech, ME, M.Tech in ECE, EEE, E&I
(Graduate/Under Graduate /Working Professional)
Program introduction
Why choose this AI & machine learning program?
Build job-ready skills for data and AI roles — SQL, Python, Excel and Power BI analytics, exploratory data analysis and machine learning — with real-world projects at every stage.
Complete data-to-ML path
SQL and Python, analytics, machine learning concepts and a capstone learning journey.
Analytics and ML in one program
Excel, Power BI and hands-on analysis for supervised and unsupervised ML.
Problem-solving focus
Competency projects and exploratory coding in Python.
Industry-standard tools
Excel, Python, Power BI, SQL, visualisation, Power BI and Pandas.
Project-based learning
Two capstone projects plus work with ML and analytics projects.
Instructor-led training
Online sessions and training by Cranes Varsity trainers.
Digital learning on CDA
Self-paced learning, recorded demonstrations and assessments.
Program outline
AI & ML curriculum: 2 phases, 8 modules, 2 capstones
Core Programming → Analytics Specialization
Core Programming SQL, Python and problem-solving
Module 1
RDBMS using MySQL
Design, query and manage relational databases using SQL, with tables, relationships and data integrity concepts.
Key topics
- SQL basics and querying data
- Creating and altering tables
- Filtering, sorting and grouping
- Joins, subqueries and aggregate functions
- Constraints, keys and normalization
- Views and practical query exercises
Module 2
Python Programming & Advanced Python
Build strong Python programming skills and apply them to data-oriented problems.
Key topics
- Python setup, syntax and variables
- Data types, operators and control flow
- Functions, modules and packages
- Lists, tuples, sets and dictionaries
- File handling and exception handling
- Object-oriented programming
- Working with libraries and practical exercises
Module 3 / Capstone
Capstone Project — Python
Practical data or coding project — from problem definition to implementation, testing and documentation.
Analytics Specialization Excel, Power BI, Power BI and machine learning
Module 4
Advanced Excel
Perform data analysis, reporting and decision-making with Excel’s advanced features.
Key topics
- IF formulas and lookup functions
- Logical functions, date and text formulas
- Data validation and conditional formatting
- Pivot tables, charts and dashboards
- Cleaning and organizing data
- Analysis and reporting best practices
Module 5
Data Analysis & Reporting using Power BI
Use interactive dashboards and business reports to turn data into meaningful insights and visualisations.
Key topics
- Data sources and Power BI Desktop
- Data modelling and Power Query
- Creating visualisations and dashboards
- Advanced business intelligence concepts
- Filters and interactive reporting
- Publish and share reports
Module 6
Exploratory Data Analysis with Pandas
Prepare, clean and explore data sets using Python and Pandas.
Key topics
- Data types, selection, filtering and indexing
- Missing values, duplicates and data quality
- Summary statistics and aggregation
- Group-by, merge, reshape and sorting
- Data visualisation and reporting
- Insights and business recommendations
Module 7
Machine Learning Fundamentals & Advanced ML
Build, evaluate and understand ML models using supervised and unsupervised learning techniques.
Key topics
- Supervised and unsupervised learning
- Data preparation and feature engineering
- Regression, classification and clustering
- Model training, testing and evaluation
- Overfitting and model validation
- Dimensionality reduction and PCA
- Practical machine learning exercises
Module 8 / Capstone
Capstone Project — Data Analytics
Complete an end-to-end analytics project, including problem definition, data preparation, analysis, visualisation and presentation.
Learner outcomes
What you’ll be able to do
Manage data with SQL — query, join and transform relational databases.
Program in Python — write, organise and debug code for practical tasks.
Solve problems — use data, logic and exploratory analysis.
Analyse in Excel — formulas, pivot tables, visualisation and dashboards.
Report with Power BI — create useful, accessible and interactive dashboards.
Explore data — clean and visualise data sets with Pandas and NumPy.
Build ML models — regression, classification, clustering and evaluation.
Deliver projects — end-to-end analysis and ML capstones.
Hands-on & capstone projects
| Project | Skills developed |
|---|---|
| Business Data Analysis | Data cleaning, reporting |
| Flight Price Prediction | Regression |
| Customer Classification | Classification algorithms |
| Customer Segmentation | Clustering and unsupervised learning |
| Forecasting & Image Processing | Image processing, ML |
| Data-driven Recommendation | Insights and recommendations |
Project selection depends on available datasets, scope and curriculum coverage.
Certification path
Final certification
Certificate name
Completion of the AI & Machine Learning program, subject to course requirements.
Assessment may include assignments, coding exercises, capstone work and completion of course activities.
Placement & job opportunities
AI and data jobs: from classroom to career
Interview readiness and placement assistance, powered by Cranes Digital Academy.
Learn
Structured materials, technical resources and self-paced revision.
Practice
Coding challenges, technical questions, projects and lab activities.
Assess
Domain assessments, skill-gap analysis and screening-test preparation.
Get placement-ready
Interview prep, technical question banks, project narratives and role opportunities.
Industry job roles
Industries hiring
IT services and product companies, banking and financial services, e-commerce and retail, healthcare, manufacturing and analytics consulting.
Hiring Client
Program FAQs
Frequently asked questions
What is the duration of the Diploma in AI & Machine Learning?
The program runs for a total of 300 hours.
Is the AI and ML course online or offline?
Training is offered in an online and/or classroom format by Cranes Varsity trainers, supported by the Cranes Digital Academy platform.
Which tools will I learn?
Learners work with MySQL, Python, Google Colab, MySQL Workbench, Excel, Power BI, Pandas and NumPy.
Does the program cover machine learning?
Yes. It includes machine learning fundamentals and advanced ML, including regression, classification, clustering, ensembles, model tuning and PCA.
What projects will I build?
Projects include business data analysis, flight price prediction, customer classification, customer segmentation, forecasting and image processing, plus recommendation and data analysis projects.
What jobs can I apply for after the course?
Roles include Data Analyst, Power BI Analyst, Python Developer, ML Engineer and Data Scientist.
