Utkarsh Minds: Data science and analytics workshops

Data science and analytics workshop in SSPU Pune

Data science and analytics students - Testimonials

One of the Best place for Upskilling in Mumbai, with Best Faculties giving their best to each of their Student.

- Parisha Bhatia

The best place to upgrade your software skills amidst experienced group of professionals.

- Heetansh Jhaveri

Previous students reviews

Utkarsh minds classes is best experience classes

I highly recommend Dr. Pranav Nerurkar and Utkarsh Minds Software Training Center. Dr. Pranav is a great professor and his patience and dedication to make every topic clear is unparalleled. He is very approachable and always works hard to help us.

Why Choose Us?

Welcome to Utkarsh, for the best data science and data analytics course in Mumbai or India where we empower individuals with essential computer skills for the digital age. Here's why choosing us is the first step towards mastering the world of technology:.

Comprehensive Course Catalog

Practical, Real-world Learning.

Experienced Instructors.

User-friendly Platform.

Flexible Learning Options.

Practical Skills for Everyday Life

Community Support

Constantly Updated Content

Affordable Learning

Empower Yourself in the Digital Era

Tier-I engineer

₹30000(120 hours)

Introduction to AI:
- Definition of AI
- Brief history of AI
- Applications of AI in various industries
- Ethical considerations and societal impacts of AI
Fundamentals of Machine Learning:
- Introduction to machine learning
- Types of machine learning: supervised, unsupervised, reinforcement learning
- Basic algorithms: linear regression, logistic regression, k-nearest neighbors
- Evaluation metrics for model performance
Basic Tools and Programming:
- Introduction to Python for AI
- Libraries like NumPy, Pandas, and Matplotlib
- Data preprocessing and manipulation
Problem Solving with AI:
- Approaches to AI problem-solving
- Search algorithms: breadth-first search, depth-first search
- Basic game theory and decision trees
Essential Mathematics:
- Linear algebra
- Calculus
- Probability and statistics basics

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Tier-II engineer

₹30000(120 hours)

Applied Machine Learning:
- Advanced supervised learning algorithms: Support Vector Machines, Decision Trees, Random Forests
- Unsupervised learning and clustering techniques: k-means, hierarchical clustering, PCA
- Introduction to deep learning and neural networks
Data Handling and Visualization:
- Advanced data processing and feature engineering
- Data visualization techniques for better insights
Natural Language Processing (NLP):
- Text preprocessing and tokenization
- Word embeddings and vector space models
- Introduction to NLP frameworks like NLTK, spaCy
Computer Vision:
- Image processing fundamentals
- Introduction to OpenCV
- Basic neural network architectures for image classification
Reinforcement Learning:
- Understanding the reinforcement learning framework
- Markov decision processes
- Basic RL algorithms like Q-learning and SARSA
Hands-on Labs and Projects:
- Building and managing a application
- Implementing a full-fledged pipeline with advanced workflows
- Deploying and managing
Soft Skills:
- Collaboration and Communication Skills
- Project Management
- Problem-Solving in Complex Systems
Additional Components:
- Periodic Assessments and Quizzes
- Real-world Case Studies and Scenarios
- Best Practices and Industry Standards
- Guest Lectures from Industry Experts

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Tier-III engineer

₹55000(240 hours)

Advanced Deep Learning:
- Deep learning frameworks (TensorFlow, PyTorch)
- Convolutional Neural Networks (CNNs) for image tasks
- Recurrent Neural Networks (RNNs) and Long Short-Term Memory Networks (LSTMs) for sequence data
- Generative models: GANs and Variational Autoencoders (VAEs)
AI Scaling and Optimization:
- Distributed computing for AI
- GPU acceleration and optimization techniques
- Model compression and efficient neural networks
Advanced NLP and Sequences:
- Attention mechanisms and transformer models
- Pre-trained models: BERT, GPT
- Sequence-to-sequence models for translation and summarization
Robotics and Control:
- Introduction to robotics and autonomous systems
- Probabilistic robotics and sensor integration
- Path planning and obstacle avoidance
AI Strategy and Policy:
- AI project management
- Discussing AI policies, privacy, and regulatory considerations
- Future trends and the direction of AI research
Hands-on Labs and Projects:
- Building and managing a application
- Implementing a full-fledged pipeline with advanced workflows
- Deploying and managing
Soft Skills:
- Collaboration and Communication Skills
- Project Management
- Problem-Solving in Complex Systems
Additional Components:
- Periodic Assessments and Quizzes
- Real-world Case Studies and Scenarios
- Best Practices and Industry Standards
- Guest Lectures from Industry Experts