How is Cranes Varsity PG diploma in Data Science and Machine Learning program?

The PG diploma in data science by Cranes Varsity is a 5-month program designed specifically for working professionals to develop practical knowledge and skills, and accelerate their data science careers.

What are the career opportunities in Data Science?

Career opportunities are very high with high pay packages compared to other domains, Roles like Data scientist, Data analyst, business analyst, Data analytics manager, Business intelligence manager and many other roles can be expected.

What are the prerequisites to learn Data Science?

Having prior knowledge of any programming language is an added advantage but not mandatory, and the basics of linear algebra are a must.

What are the prerequisites for Machine Learning Course enrollment?

Having a good knowledge of Python Programming concepts, and a good hold on linear algebra.

Can I learn Machine Learning Online?

Yes, you can learn Machine Learning Course completely online.

PG Diploma in Data Science | Data Science Courses In Bangalore

PG Diploma in Applied Data Science with Deep Learning

100% JOB Assured with Globally Accepted Certificate

Duration: 6 Months
Eligibility: BE,CS, BCA

Course level: Intermediate

Modules

Foundational Modules

Database – 40 hrs.

RDBMS using MySQL

Core Programming – 140 hrs.

Python Programming & Advanced Python
Problem Solving and Data Structures using Python

Data Analytics – 120 hrs.

Advanced Excel
Data Analysis & Reporting using Power BI
Exploratory Data Analysis with Pandas

SPECIALIZATIONS:

Machine Learning – 120 hrs.

Machine Learning Fundamentals & Advanced ML
ML System Design & Deployment (MLOps)

Advance AI – 120 hrs.

Deep Learning using TensorFlow
Natural Language Processing
Generative AI & Agentic AI

AI Applications – 40 hrs.

AI Developer Tools (GitHub Copilot, Cursor.ai)
Prompt Engineering & AI Ethics

Projects

Apply statistical methods to make decision in various business problems, including bank, stock market etc.
Apply regression to predict future flight price
Apply classification to classify customer
Use clustering to cluster banking customers
Computer vision projects like Face recognition, Image Quality Improvement etc.
Gesture recognition captured through image or video data
Identify the Gender using streamlit

Platform:

Anaconda Distribution Jupyter, Spyder, Google Colab, Pycharm
MySQL
Microsoft Excel
POWERBI.
Libraries: Pandas, Matplotlib, Seaborn
ML Libraries: sklearn, Tensorflow, Pytorch, NLTK

Course Curriculum Table

Database
RDBMS using MySQL – 40 hrs. – 10 Days – 2 weeks
Introduction to databases and RDBMS, Database creation, concept of relation and working examples	Creating tables, Design view of the table, Alter table operations & Key Constraints	Read, update and delete operations on tables, Working with nulls
Querying tables: SELECT statement, examples and its variations	Filtering, Sorting, Predicates and working examples	Joins in SQL and working examples, Insert, Update, Delete operations
Scalar functions in SQL and working examples	SQL set-based operations and data aggregation	Subqueries, Normalization & De-normalization
Views and Temporary tables	Transactions in SQL	SQL Programming, Stored Procedures, Cursors in SQL
Core Programming
Python Programming & Advanced Python – 80 hrs. – 20 Days – 4 weeks
Introduction to Python, Python Data types and Conditions, Control Statements	Functions, Default arguments, Functions with variable args, Scope of Variables	Global specifier, Working with multiple files
List and Tuple, List Methods, List Comprehension	Map and Filter functions, String operations, Conditional List Comprehension	Set and Dictionary, Exception Handling, File Handling
Object-Oriented Programming, Overloading, Operator Inheritance	Regular Expression, Finding Patterns of Text, Meta Characters	Testing Fundamentals, Unit Testing, Working with JSON
Decorators	Iterators	Generators
Problem Solving and Data Structures using Python – 60 hrs. – 15 Days – 3 weeks
Time and Space Complexity	Utopian Tree, Viral Advertising, Birthday Cake Candles, Migratory Birds, Kaprekar Number	Pangram String, Anagram String, Palindrome, Index, Array Rotation
Data Analytics
Advanced Excel – 40 hrs. – 10 Days – 2 weeks
Introduction to MS Excel, Fill Series, Flash Fill, Logical Functions – IF, AND, OR, NOT, IFERROR	Text Functions, Date Functions, Statistical Functions	VLOOKUP & HLOOKUP, Index & Match Functions, Sorting & Filtering Data
Pivot Table, Data Validation, What-if Analysis	Charting Techniques, Interactive Dashboard Creation	Data Analytics Project using Excel
Data Analysis & Reporting using Power BI – 20 hrs. – 5 Days – 1 week
Introduction to Power BI, Getting started with Power BI Desktop	Data Modelling, Advanced Data Transformation	Creating Visualization, Dashboards & Best Practices
Conditional Formatting, Data Cleaning	Exploratory Data Analysis	Table Formatting & Reporting
Exploratory Data Analysis with Pandas – 40 hrs. – 10 Days – 2 weeks
NumPy Vectorization, Broadcasting, Slicing of Matrices	Filtering, Stacking of Arrays, Matrix Calculations	Pandas Series & DataFrames, Data Cleaning & Handling Missing Data
Grouping & Aggregation, Merging DataFrames (concat, merge)	Sorting Data, Importing CSV & Excel files	Creating Graphs using Matplotlib, Customizing Plots with Seaborn/Plotly
End-to-End Machine Learning Model Development using scikit-learn and real-world datasets
Specialization
Machine Learning Fundamentals & Advanced ML – 80 hrs. – 20 Days – 4 weeks
Introduction to Machine Learning, Regression, Logistic Regression	Supervised & Unsupervised ML, Simple & Multiple Linear Regression	Naïve Bayes, Decision Trees, Train-Test Split
KNN, Random Forest, Clustering (types, evaluation, Elbow Plot)	Regression Optimization – Forward Elimination, Grid Search CV	Classification Models – Ensemble Modeling, Bagging, Boosting (ADA Boost)
Model Evaluation – KFold, Stratified KFold, Performance Metrics	Regularization (L1, L2), SVM, PCA	Stacking, Voting, Dimensionality Reduction
ML System Design & Deployment (MLOps) – 40 hrs. – 10 Days – 2 weeks
MLOps Fundamentals, Reproducible Project Setup	Data Versioning & Validation, Experiment Tracking & Model Registries	Feature Store, CI/CD Pipelines, Model Deployment & Monitoring
Advanced Deployment Strategies, Production Model Monitoring	ML Infrastructure Scaling, Pipeline Orchestration	End-to-End MLOps Project
Advanced AI
Deep Learning using TensorFlow – 40 hrs. – 10 Days – 2 weeks
Introduction to Deep Learning, Performance Metrics for ANN	Neural Networks, CNN Architecture & Types	Project-based CNN Implementation
Need for Hardware & Data Augmentation	Basics of Image Processing, Batch Normalization, Dropout	OpenCV Library, Image Enhancement & Filtering
Edge Detection, Morphology, Forward & Backward Propagation	CNN for Computer Vision, TensorFlow, PyTorch, Keras	RNN, LSTM, Basic OpenCV Functions
Natural Language Processing – 40 hrs. – 10 Days – 2 weeks
Introduction to NLP, Applications & Understanding Text	Text Encoding, Word Frequencies, Stop Words, Bag of Words, TF-IDF	Stemming, Lemmatization, Canonicalisation, Phonetic Hashing
Spell Correction, PMI, Word2Vec, Gensim	NER, POS Tagging, Dependency Parsing, Syntactic Analysis	Semantic Similarity, Sentence Embeddings, BiLSTM
Generative AI & Agentic AI – 40 hrs. – 10 Days – 2 weeks
Introduction to Gen AI, Rule-based vs Neural Generation	GANs, VAEs, Transformers, Applications & Ethics	FastText, Sentence Embeddings, Visualizing Embeddings
Prompt Engineering, Zero/Few-Shot Prompting	Chain-of-Thought Style, System & User Prompts	Common Prompt Engineering Mistakes
AI Applications
AI Developer Tools (GitHub Copilot, Cursor.ai) – 20 hrs. – 5 Days – 1 week
AI Assistant Fundamentals	Mastering GitHub Copilot	Exploring Cursor.ai
Effective Code Prompting	AI Debugging & Testing	Ethics & Best Practices
Prompt Engineering & AI Ethics – 20 hrs. – 5 Days – 1 week
Prompting Fundamentals	Advanced Prompting Techniques	Bias, Fairness & Mitigation
AI Transparency & Accountability	Privacy & Data Governance	Responsible AI Practices

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FAQs

What is the duration of the PG Diploma in Data Science course?

The course duration is 6 months, covering both foundational and advanced data science modules.

Who is eligible to apply for the course?

The program is open to graduates in BE,CS,BCA from any engineering stream.

Is prior programming experience required?

Not mandatory, but basic knowledge of programming or mathematics/statistics is recommended for better understanding.

What topics are covered in the curriculum?

The course includes:

Python Programming & Data Structures
Data Analytics (Excel, Power BI, Pandas)
SQL & RDBMS
Machine Learning
Deep Learning & NLP
Generative AI & Prompt Engineering
Hands-on Project Work

What tools and platforms will I learn?

You will work with tools like:

Jupyter, Google Colab, PyCharm
MySQL, Excel, Power BI
Python Libraries: Pandas, NumPy, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK

Are the classes conducted online or offline?

The format is not explicitly stated. It’s best to contact Cranes Varsity directly to confirm if the mode is online, offline, or hybrid.

Is this a government-recognized or university-affiliated diploma?

While the program offers a "globally accepted certificate", specific government or university affiliations are not mentioned. You should inquire directly for accreditation details.