Applied Data Science with Deep Learning -Tailored for Working Professionals

Duration: 500 Hrs.
Eligibility: B.Tech & M.Tech CS

Diploma in Data Science with Deep Learning

100% JOB Assured with Globally Accepted Certificate

Eligibility: BE, B.Tech, ME, M.Tech

If you are a working professional aspiring to build a successful career in Data Science, AI, and Machine Learning, Cranes Varsity offers a comprehensive, industry-aligned Advanced Diploma / PG Diploma in Applied Data Science with Deep Learning.

This career-focused program is designed to strengthen technical foundations, provide intensive hands-on project experience, and ensure complete interview readiness—enabling you to confidently transition into high-demand, data-driven roles.

From core programming fundamentals to advanced Deep Learning and Generative AI applications, the curriculum is carefully structured to match real-world industry expectations and hiring standards.

Program Overview

Advanced Diploma in Data Science

Duration: 300 Hours

Learning Modes:

  • Offline – 4 Hours per Day
  • Online – 2 Hours per Day
  • Hybrid Mode
PG Diploma in Applied Data Science with Deep Learning
Duration: 500 Hours
Learning Modes:
  • Offline – 4 Hours per Day
  • Online – 2 Hours per Day
  • Hybrid Mode

Both programs follow a structured learning pathway that progresses from foundational programming to production-level model development and deployment.

Why Choose This Program?

Today’s organizations expect working professionals to go beyond theoretical knowledge and demonstrate practical expertise in real-world data science applications. Companies look for professionals who can:

• Build and implement machine learning models
• Work with real-world datasets and perform data analysis
• Develop and deploy production-ready solutions
• Clearly explain models and approaches during technical interviews
• Apply data-driven thinking to solve real business problems

This program is designed to help working professionals upskill effectively by providing the technical depth, hands-on experience, and strong project portfolio needed to grow in the competitive Data Science and AI job market.

AD – Diploma in Data Science with AIML

Modules

Foundational Modules

Database

  • RDBMS using MySQL

Core Programming 

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

Certification – Python Programming

Data Analytics

  • Advanced Excel
  • Data Analysis & Reporting using Power BI
  • Exploratory Data Analysis with Pandas
  • Capstone project – Data Analysis

Certification – Diploma in Data Science with AIML 

Projects

  • Data Cleaning & Exploratory Data Analysis (EDA)
  • Sales & Business Data Analysis
  • Banking & Stock Market Data Analysis
  • Regression: Flight Price Prediction
  • Classification: Customer Segmentation / Churn
  • Capstone Project – Data Analysis

Platform:

  • Python (Pandas, NumPy, Matplotlib, Seaborn)
  • Jupyter Notebook / Spyder (Anaconda)
  • MySQL
  • Advanced Excel
  • Power BI
  • Google Colab

PG Diploma in Applied Data Science with Deep Learning

Modules

Foundational Modules

Database:

  • RDBMS using MySQL

Core Programming

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

Certification – Python Programming

Data Analytics

  • Advanced Excel
  • Data Analysis & Reporting using Power BI
  • Exploratory Data Analysis with Pandas
  • Capstone project – Data Analysis

Certification – Diploma in Data Science with AIML

SPECIALIZATIONS

Machine Learning Database:
  • Machine Learning Fundamentals & Advanced ML
Advance AI
  • Deep Learning using TensorFlow
  • Natural Language Processing
  • Generative AI & Agentic AI
  • Capstone Project – AI
Certification – PG Diploma in Applied Data Science with Deep Learning

Experiential Project-Based Learning

  • An end-to-end machine learning model development using scikit-learn and real-world datasets

Projects

  • End-to-End Machine Learning Model
  • Advanced Regression & Classification
  • Clustering & Time Series Forecasting
  • Computer Vision (Face & Gesture Recognition)
  • NLP & Generative AI Applications
  • Streamlit-Based AI App
  • Capstone Project – AI

Platforms

  • Python (Anaconda, PyCharm, Google Colab)
  • scikit-learn
  • TensorFlow, PyTorch
  • NLTK
  • Streamlit
  • MySQL
Core Programming
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 and working examples Scalar functions in SQL and working examples
SQL set-based operations and data aggregation Sub-queries in SQL Normalization and de-normalization: Views and Temporary tables Transactions in SQL SQL programming Creating stored procedures, Cursors in SQL
Learners Outcome
Design, query, and manage relational databases using SQL with transactions, procedures, and data integrity constraints.
Python Programming & Advanced Python – 80 hrs. – 20 Days – 4 weeks
Introduction to Python Python Data Types and Conditions Control Statements
Python Functions Default arguments Functions with a variable number of args
Scope of Variables Global specifier Working with multiple files
List and Tuple List Methods List Comprehension
Map and filter functions String List comprehension with conditionals
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
Learners Outcome
Develop robust Python applications using core, advanced, and object-oriented concepts with real-world data handling.
Problem Solving and Data Structures using Python – 40 hrs. – 10 Days – 2 weeks
Time and Space Complexity Utopian Tree Viral Advertising
Birthday Cake Candles Migratory Birds Kaprekar Number
Pangram String and Anagram String Palindrome Index Array Rotation
Learners Outcome
Apply algorithmic thinking and complexity analysis to solve logical and competitive programming problems using Python.
Certification - Certification in Python Programming
Analytics Specialization
Advanced Excel – 40 hrs. – 10 Days – 2 weeks
Introduction to MS-Excel Fill Series, Flash Fill Logical Functions – IF, AND, OR, NOT, IF Error
Text Functions Date Functions Statistical Functions
VLOOKUP and H-Lookup Index and Match Functions Sorting and Filtering Data
Pivot Table Data Validation What-if Analysis
Charting techniques in Excel Interactive dashboard creation Data analytics project using Excel
Learners Outcome
Perform data analysis, reporting, and dashboard creation using advanced Excel functions and analytical tools.
Data Analysis & Reporting using Power BI – 40 hrs. – 10 Days – 2 weeks
Introduction to Power BI Getting started with Power BI Desktop Data modelling in Power BI
Creating visualization Advanced data transformation Power BI Dashboards
Data Visualization Best practices Table and Conditional Formatting Data Cleaning and Transformation
Learners Outcome
Build interactive dashboards and business reports using data modeling, visualization, and transformation techniques
Exploratory Data Analysis with Pandas – 40 hrs. – 10 Days – 2 weeks
NumPy Vectorization Broadcasting
Slicing of Matrices Filtering Array Creation Functions
NumPy Functions across axis Stacking of arrays Matrix Calculation
Pandas Series Data Cleaning Handling Missing Data
Pandas Data frame Selection Data (loc, iloc) Filtering Data Frames
Working with Categorical Data Grouping & Aggregation Merging Data Frame (concat, merge)
Sorting Data Frames Importing csv files Importing Excel Files
Creating graphs using Matplotlib Customizing Plots Seaborn, PlotLy
Learners Outcome
Analyze, clean, and visualize large datasets using NumPy, Pandas, and Python visualization libraries.
Capstone project - Data Analysis – 20 hrs. – 5 Days – 1 week
Certification - Diploma in Data Science with AIML
AI Specialization
Machine Learning Fundamentals & Advanced ML – 80 hrs. – 20 Days – 4 weeks
Introduction to Machine Learning Regression Logistic regression
Supervised machine learning Simple linear regression Naïve Bayes Classification
Unsupervised machine learning Multiple linear regression Decision tress and its types
Train test split the data Performance measure for regression K Nearest Neighbour Classification
ML Workflow for project implementation Classification and types Performance Measure for Classification
Random Forest, Clustering and types Evaluate clustering results, Elbow Plot
Optimizing regression models with forward elimination, grid search cv Improving classification models with Ensemble modeling Model evaluation strategies (KFold, Stratified KFold)
Regularization L1 and L2 regularization Bagging Boosting techniques: ADA boost
Hyperparameter Tuning, SVM Stacking and Voting Dimensionality Reduction with PCA
Deep Learning using TensorFlow – 40 hrs. – 10 Days – 2 weeks
What is Deep Learning
Performance measure for ANN
Building project based on CNN
Deep Learning Methods
Need for Hardware’s in Deep Learning
Need for Data augmentation
Deep Learning Application
Basics of image processing
Batch Normalization, dropout
Artificial Neural Network
Opencv library
Object detection with CNN
Hidden Layers
Image reading, writing, enhancement
Object recognition with CNN
Activation Function
Edge detection, filtering, morphology
Forward and Backward propagation
CNN for computer vision
CNN architecture and its types
Tensorflow, PyTorch, Keras
Recurrent Neural Network (RNN)
Long- Short term Memory (LSTM)
Basic Open CV Functions
Learners Outcome
Design and implement deep learning models for computer vision and sequence-based applications.
Natural Language Processing – 20 hrs. – 5 Days – 1 week
Introduction to NLP
NLP: Areas of Application
Understanding the Text
Text Encoding
Word frequencies and stop words
Bag of words representation
Stemming and Lemmatization
TF- IDF representation
Canonicalisation
Phonetic Hashing
Spell Corrector
Point wise mutual Information
Gensim, Word2Vec
Word Embeddings
Named Entity Recognition (NER) and Parts of Speech Tagging
Dependency Parsing and Syntactic Analysis
Semantic Similarity and Sentence Embeddings
Bidirectional LSTM
Learners Outcome
Develop NLP solutions for text processing, representation, and semantic understanding.
Generative AI & Agentic AI – 40 hrs. – 10 Days – 2 weeks
Introduction to Gen AI
Rule-based vs neural generation
Generative Adversarial Network
Variable Auto Encoder
Transformers
Application of Generative AI, Ethics
FastText and subword models
Sentence embeddings and similarity
Encoding long text documents
Visualizing embeddings with tools
Prompt Engineering
Zero – shot and few–shot prompts
Learners Outcome
Create and apply generative AI models, embeddings, and prompt-engineering techniques responsibly.
Capstone project – AI – 20 hrs. – 5 Days – 1 week

Hiring Partners

FAQs

Our Data Science courses are designed for: 

  • Graduates in fields like Computer Science, Statistics, Mathematics, Engineering, and related areas. 
  • Working professionals looking to transition into data science roles or enhance their analytics skills. 
  • Business analysts seeking to deepen their understanding of data-driven decision-making. 

Research professionals wanting to apply data science techniques in their work. 

  • PG Diploma in Artificial Intelligence and Data Science-6 Months 
  • Advanced Diploma in Data science with Deep learning-4 Months 

Eligibility criteria typically include: 

  • A bachelor’s degree in computer science, Statistics, Mathematics, BCA, MCA or a related field. 
  • Basic programming knowledge in languages like Python or R is advantageous but not mandatory for beginners. 

By completing a Data Science course at Cranes Varsity, you will acquire skills such as: 

  • Core programming -RDBMS using MySQL, Python Programming
  • Analytics Specialization -Exploratory Data Analysis using Pandas, Data Visualization with Reporting, Power BI for Modern Analytics
  • Experiential Project Based Learning-An end-to-end machine learning model, development using scikit-learn and real-world datasets
  • AI Specialization -Machine Learning, Deep Learning, Natural Language Processing, Generative AI

We teach Python and SQL as the core programming languages in the Data Science course. Python is used for data analysis, machine learning, and visualization, while SQL is essential for working with databases and querying structured data.

You’ll gain hands-on experience with a variety of tools, including:

  • Jupyter Notebook and Google Colab for interactive coding
  • Anaconda for environment and package management
  • Git & GitHub for version control
  • Power BI and Excel for data visualization
  • Popular libraries like pandas, NumPy, Matplotlib, seaborn, scikit-learn, TensorFlow, and NLTK for machine learning and NLP 

  • Exploratory Data Analysis (EDA)
  • Machine Learning models (e.g., classification, regression)
  • Sentiment Analysis and Text Processing (NLP)
  • Time Series Forecasting
  • Interactive Dashboards and Visualizations 

Yes, Cranes Varsity offers comprehensive placement support to students. We have connections with numerous tech companies and startups. Our placement assistance includes: 

  • Resume building and interview preparation. 
  • Access to job opportunities in data science, analytics, and related fields. 
  • Networking opportunities with industry professionals. 

Upon completing a Data Science course at Cranes Varsity, you can pursue roles such as: 

  • Data Scientist 
  • Data Analyst 
  • Machine Learning Engineer 
  • Business Intelligence Analyst 

Upon successful completion of the course, all students will receive a Postgraduate Diploma Certificate issued by Cranes Varsity.

Our curriculum is designed in collaboration with industry experts to meet the latest trends and demands in the data science field. We emphasize: 

  • Practical training through projects and real-world applications. 
  • Industry-relevant case studies to develop problem-solving skills. 
  • Guest lectures and workshops from data science professionals. 

Cranes Varsity emphasizes a hands-on learning approach. While theoretical concepts are crucial, a significant portion of the course focuses on practical lab sessions, projects, and applications of data science tools and techniques. 

Assessments in the Data Science courses include: 

  • Hands-on coding assignments and projects. 
  • Quizzes and exams to test theoretical understanding. 
  • Capstone projects where students apply their knowledge to solve real-world problems. 

Yes, Cranes Varsity provides online learning support for Data Science courses, including: 

  • Access to recorded lectures and tutorials. 
  • Virtual labs for practical experimentation. 
  • Online assignments and assessments. 
  • Interactive Q&A sessions with faculty. 

To enroll in a Data Science course: 

  • You can fill out the application form and the dedicated admission counsellor will contact you.. 
  • You can also visit our campus for direct inquiries and enrollment assistance. 

Our trainers are seasoned professionals and industry experts with over 10+ years of relevant experience teaching the AI and ML certification course. Each of them has gone through a rigorous selection process that includes profile screening, and technical evaluation before they are certified to train for us. We also ensure that only trainers with a high alumni rating continue to train for us. 

Yes, Cranes Varsity offers scholarships and financial assistance for eligible students based on merit and need. We also provide early-bird discounts for those who enroll before specified deadlines. 

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