Applied Data Science with Deep Learning -Tailored for Working Professionals
Duration: 6 months (Online)
Eligibility: B.Tech & M.Tech CS
Diploma in Data Science with Deep Learning
100% JOB Assured with Globally Accepted Certificate
Overview
If you’re a working professional looking to transition into the data-driven tech industry or upskill in cutting-edge analytics and AI, Cranes Varsity offers a specialized pathway with the Diploma in Applied Data Science with Deep Learning, designed to fit seamlessly into your busy schedule.
This data science course for working professionals is delivered through flexible and accessible formats—including data science course online options, live interactive sessions, and a fully online learning platform. It’s one of the best online data science programs for engineers and professionals seeking real-world skills and career advancement.
As one of the top-rated institutes for data science training in Bangalore, Cranes Varsity has consistently empowered professionals to become industry-ready data scientists.
Why Choose This Program?
This Program is thoughtfully designed for those who want to stay competitive in today’s data-centric world. Whether you want to solidify your foundations or explore advanced topics like Deep Learning and AI, this program offers:
- Data science course online – Learn flexibly from anywhere, at your own pace
- Evening batch data science course – Perfect for working professionals balancing work and study
- Hands-on projects with real-time datasets – Apply your knowledge in practical scenarios
- Industry-focused curriculum – Stay aligned with the latest tools like Python, TensorFlow, Scikit-Learn,
Modules
Database – 40 hrs.
- RDBMS using MySQL
- Python Programming & Advanced Python
- Problem Solving and Data Structures using Python
- Advanced Excel
- Data Analysis & Reporting using Power BI
- Exploratory Data Analysis with Pandas
SPECIALIZATIONS:
- Machine Learning Fundamentals & Advanced ML
- ML System Design & Deployment (MLOps)
- Deep Learning using TensorFlow
- Natural Language Processing
- Generative AI & Agentic AI
- 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
| 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 |
Hiring Partners
FAQs
Who can benefit from the Data Science courses at Cranes Varsity?
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.
What is the duration of Data Science courses at Cranes Varsity?
- PG Diploma in Artificial Intelligence and Data Science-6 Months
- Advanced Diploma in Data science with Deep learning-4 Months
What are the eligibility criteria for enrolling in Data Science courses?
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.
What skills will I learn from the Data Science courses?
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
Which programming languages are taught in Data Science course?
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.
What tools and software will I work with during the Data Science course?
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
What types of projects can I expect to work on during the Data Science course?
- Exploratory Data Analysis (EDA)
- Machine Learning models (e.g., classification, regression)
- Sentiment Analysis and Text Processing (NLP)
- Time Series Forecasting
- Interactive Dashboards and Visualizations
Does Cranes Varsity provide placement assistance for Data Science courses?
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.
What job roles can I pursue after completing a Data Science course?
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
What certificates will I receive on completion of the training program?
Upon successful completion of the course, all students will receive a Postgraduate Diploma Certificate issued by Cranes Varsity.
How does Cranes Varsity prepare students for industry requirements in Data Science?
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.
Are the Data Science courses at Cranes Varsity more theoretical or practical?
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.
What are the assessments like in the Data Science courses?
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.
Is there online support for the Data Science courses?
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.
How can I enroll in a Data Science course at Cranes Varsity?
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.
Who are your trainers for the program and how are they selected?
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.
Are there scholarships or discounts available for Data Science courses?
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.
Testimonials
On completing my B. Tech in Computer Science and Engineering and as a fresher it was so difficult to get a better career. So, I joined Cranes Varsity for PG Diploma in Data Science and it really helped me a lot. I have learned a lot from the institution. The trainers are very professional and have in-depth knowledge about the subjects. The placement team is also very cooperative and provided me with good opportunities. I got placed in Onward Technologies Thanks to Cranes Varsity for helping me to get a better job.
I joined Cranes Varsity, in August 2021, after my engineering hoping to start my career in the Data Science domain. The trainers here are very supportive and have profound knowledge in modules like Basic and advanced python, DAV, ML, DL, Tableau, etc. They also evaluate student performance through mock tests and interviews. They provide a significant amount of placement opportunities in reputed companies. I am extremely grateful to the placement team, because of them I got placed in Kyndryl. If you are a fresher hoping to get a job in your favorite domain then the Cranes Varsity is the place for you.
I have completed my B.E in Mechatronics. As a fresher, it was very difficult to get a better career. So, I joined Cranes Varsity for doing Data Science Training Program and it has really helped me a lot. I learned a lot from Cranes Varsity. The trainers are very professional and have in-depth knowledge about the subjects. The placement team is also very cooperative and they provide a lot of opportunities. At last, I got placed in Tek systems Thanks to Cranes Varsity for helping me to get a better job.
I have completed B E in Mechatronics. I joined this institute in September 2021 for PG Diploma in Data Science in Cranes Varsity. The Trainers are good. Mock tests are regularly conducted to improve our technical and aptitude skills. They provide a many numbers of placement opportunities to all and they are very supportive and guide you for placement I got placed in TataElxsi. If we put in your right efforts in the training, you will get 100% placements.
I joined Cranes Varsity for Data Science Certification Courses after my engineering. I am 2021 passed out and I learned to start from basic python to advance python, Data analytics and visualization, RDBMS, ML, Tableau, etc. They provide multiple placement opportunities to all and they are very supportive and guide you for placement. I got placed in EY a big4 company with a very good package for a fresher. So if u need to learn new things and need placement Cranes Varsity is the best place for you.
I came to know about Cranes Varsity through Career labs as it approached my institute. Teaching in Cranes Varsity is good and for the Data Science Online Course, they covered modules like Python, Advanced Python, DAV, RDBMS, Tableau, Machine Learning and DL, Web technology, and Cloud Computing. Also, they provide many placement opportunities. They regularly have module and placement tests so that we can test our knowledge and do better in actual placements. I got placed in Genpact
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