AI – Machine Learning Certification Course in Pune with AI & ChatGPT
- Earn Industry-recognized certification
- Build real-time projects with industry-aligned tools
- Live Interactive sessions from industry veterans
- Updated curriculum designed for AI-era
- Dedicated Job Assistance and Resume Building
Success Stories – They Believed, Learned & Achieved!
Our learners are working in leading organizations
Gain industry-ready skills and earn an official certificate from DataFlair.
Full Stack AI and Machine Learning Course in Pune Curriculum
- Understanding Machine Learning
- AI and ML Differences
- Machine Learning Classification
- Essential ML Terminologies
- Working with NumPy, Pandas & Matplotlib
- Features and Labels in ML
- Training and Testing in ML
- Overfitting vs. Underfitting
- Mathematical Foundations
- Algorithm Survey & Use Cases
- The Machine Learning Workflow
- Popular Machine Learning Algorithms
- Reinforcement Learning
- Types of Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Machine Learning in Finance and Banking
- Machine Learning in Retail
- Machine Learning in Healthcare
- Machine Learning in Logistics and Supply Chain
- Machine Learning in the Technology Industry
- Machine Learning in Manufacturing
- Machine Learning in Agriculture
- Introduction to Regression
- Regression Real-World Use Cases
- Types of Regression Problems
- Linear Regression
- Evaluation Metrics
- Common Challenges with Regression
- Linear vs Polynomial vs Ridge vs Lasso Regression
- Regression Industry Applications
- Introduction to Classification
- Comparison of Regression vs. Classification
- Classification Real-World Applications
- Types of Classification Problems
- Data Preparation for Classification
- Label Encoding vs One-Hot Encoding
- Feature Scaling in ML
- Train-Test Split in ML
- Handling Imbalanced Data in Classification
- Model Evaluation Metrics in Classification
- Accuracy in Classification
- Precision, Recall, and F1-Score in Classification
- Confusion Matrix in Classification
- ROC Curve and AUC Score in Classification
- Overfitting & Underfitting in ML
- Regularization Techniques in Classification
- What is k-NN?
- How k-NN Works
- KNN Distance Metrics
- Choosing the Right ‘k’ in KNN
- Data Preparation for KNN
- Categorical Features Handling in KNN
- Strengths and Limitations of KNN
- Evaluation Metrics in KNN
- KNN Model Tuning
- Cross-Validation in KNN for Optimal ‘k’
- Understanding Decision Tree
- Decision Trees Types
- Parts of a Decision Tree
- Decision Tree Splitting Criteria
- Gini Impurity in Decision Tree
- Entropy & Information Gain in Decision Tree N
- Advantages and Limitations of Decision Trees
- Pre-Pruning and Post-Pruning in Decision Trees
- Decision Tree Evaluation Metrics
- Decision Tree Hyperparameter Tuning
- Decision Tree Cross-Validation
- Understanding Random Forest
- Benefits of using Random Forest over a Single Tree?
- Logics Behind Random Forest
- Working of Random Forest
- Random Forest Hyperparameters
- Random Forest Advantages and Limitations
- Random Forest Use Cases
- What does unsupervised learning mean?
- Comparing Supervised vs unsupervised learning
- Where to use Unsupervised learning
- Application of Unsupervised learning
- Popular Algorithms in Unsupervised Learning
- Real-world use cases of Unsupervised learning
- Evaluation Metrics
- What are Clustering Algorithms?
- What is Clustering?
- Differences Between Supervised and Unsupervised Learning
- Classification vs Clustering
- K-Means Clustering
- K-means Clustering: Real-world industry use cases
- Elbow method in K-means Clustering
- Hierarchical Clustering
- Agglomerative vs Divisive Approach in Hierarchical Clustering
- Hierarchical Clustering: Real-world industry use cases
- Dimensionality Reduction
- Introduction to Enterprise Applications
- Predictive Modeling & Segmentation
- Personalization Engines
- Time Series & Anomaly Detection
- What is Scikit-Learn and Why is it Important?
- Features of Scikit-Learn for Machine Learning
- Installing Scikit-Learn and Setting Up the Environment
- Understanding the Machine Learning Workflow with Scikit-Learn
- Deep Learning vs Machine Learning
- Knowledge on Deep Learning
- Deep Learning Case Studies in Industry
- Why Deep Learning?
- Need for Deep Learning in Industry
- Why Deep Learning is in Demand
- Key Deep Learning Terminologies
- What are Artificial Neural Networks
- History of Deep Learning
- Applications of Deep Learning
- Convolutional Neural Networks
- Activation Functions in Deep Learning
- Optimizers in Deep Learning
- ResNet50
- Vanishing gradients
- Transfer Learning
- DenseNet121
- Recurrent Neural Networks
- ANN vs CNN vs RNN
- LSTM
- RNN vs LSTM
- LSTM in deep learning
- Deep learning architectures: perceptron, feedforward neural networks
- Activation functions and network initialization
- Backpropagation algorithm and training neural networks
- Optimization techniques for deep learning: Adam, RMSprop, etc.
- Perceptron & Feedforward Designs
- Activation & Initialization
- Backpropagation & Optimizers
- Understanding CNNs for image analysis
- Convolution and pooling layers
- Object detection and image segmentation
- Transfer learning with pre-trained CNNs
- RNN fundamentals: architecture, hidden states, and memory cells
- Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRUs)
- Sequence generation and language modeling
- Applications of RNNs: text generation, machine translation, speech recognition
- Introduction to OpenCV?
- Installing OpenCV Using pip
- Setting Up OpenCV in PyCharm
- How to Install and Use OpenCV in PyCharm
- Using imread() and imwrite() Functions to Load and Save Images
- Getting OpenCV Suggestions in PyCharm
- Displaying Images in OpenCV
- Resizing Images with OpenCV
- Rotating Images in OpenCV
- Merging Multiple Images
- Flipping Images Using Bitwise NOT in OpenCV
- Changing Image Colors with cvtColor() in OpenCV
- Capturing Video with OpenCV
- Recording Video from Webcam
- Drawing Lines on Images and Videos
- Drawing Circles on Images
- Adding Text to Images in OpenCV
- Difference Between add() and addWeighted() Functions
- Working with Image Properties (Shape & Size)
- Cropping Images with OpenCV
- Using hconcat() and vconcat() for Image Concatenation
- Blurring Images in OpenCV
- Creating a Graphical Image Rotation App with Tkinter
- Showing Multiple Dynamic Images with Tkinter
- Dynamically Resizing Images Using Tkinter
- Basic Video Operations with Dialog Box in OpenCV
- Resizing Videos and Images with Specified Dimensions
- Drawing Various Shapes in OpenCV
- Applying Image Transformations in OpenCV
- Converting BGR Images to RGB in OpenCV
- Using Different Color Codes in OpenCV
- Detecting Edges Using Canny Edge Detection in OpenCV
- What does Natural Language Processing mean?
- Applications of NLP
- Text Preprocessing
- Text Classification
- Sentiment Analysis
- Artificial Intelligence Fundamentals
- Understanding Gen AI
- Agentic AI Essentials
- Historical evolution: From reactive systems to proactive agents
- Working with Agentic AI
- Applications of Agentic AI
- Agent vs. Model vs. Tool: Understanding the distinction
- Agentic AI vs AI Agents
- Multi-Agent Systems
- Core characteristics of AI agents: autonomy, proactivity, adaptability
- Real-world use cases of AI agents
- Agent architectures
- Open-source agent frameworks
Objectives of the AI and Machine Learning Course in Pune
After completing this online Machine Learning course in Pune, you will:
- Learn about the core concepts of Machine Learning and the reasons behind its use in almost every industry.
- Master important Machine Learning algorithms by hands-on experience in Linear Regression, Decision Trees, K-Nearest Neighbours, and more.
- Understand how to collect, clean, and prepare raw data for building accurate and reliable ML models.
- Develop problem-solving skills by applying Machine Learning in real-time projects such as sales prediction, customer segmentation, fraud detection, and more.
- Explore how to train models, measure their performance, and improve accuracy using practical tools and libraries like Python, Pandas, and Scikit-Learn.
This best AI/ML course in Pune is designed to make you ready for the industry with skills that you can apply immediately after learning.
Why should you learn AI and Machine Learning?
Machine Learning is not just a trending topic; it has now become a powerful skill that is highly demanded by employers. Whether it’s predicting customer behavior, detecting fraud, or powering self-driving cars, ML is behind everything.
You will learn the following in these AI & Machine Learning classes in Pune:
- Learn ML from scratch as we cover from basics to advanced concepts.
- You’ll practice with real-time datasets to increase understanding of how thighs work.
- Build job-ready skills as we teach tools and concepts that are used in industry today.
- Get exciting job opportunities and competitive salaries by adding Machine Learning to your skillset.
This is the best AI/ML course to start your career and learn the working mechanism behind smart technologies with real impact.
What is Machine Learning?
Machine Learning is like permitting computers to learn from experiences similar to humans. In contrast to providing commands at each step, we feed computers with bulk data and allow them to fetch patterns out of it independently. It gets experienced over time and makes better decisions and predicts future outcomes without being explicitly programmed at each step.
Machine Learning is not just about writing code; you are training machines to learn and improve with time. Machine Learning unlocks thrilling and effective opportunities for customer behaviour prediction, fraud detection, or building smart applications.
Do you want to see how machines can learn and make your life smarter? Dive into the technology world with this course.
What to do before you begin?
This AI & Machine Learning training in Pune is designed for all the curious people, whether they are a college student exploring career options, a working professional aiming to upskill, or someone completely new to this field. To learn smoothly throughout the course, you need to have the following:
- Some programming experience, like knowing the basics of Python or some other programming language, will help, but you don’t have to be a coding expert.
- Knowledge about basic math concepts, such as simple algebra, probability, and basic statistics, is enough. No worries, if you don’t have an idea about this, we will guide you when such topics or queries arise during the course.
- For anyone with a problem-solving mind, this course will be very fun and interesting.
Machine Learning experience is not required. Starting from the basic concepts and gradually moving towards advanced concepts, so that you develop practical learning skills that can be applied immediately.
Who should opt for these online AI / ML classes in Pune?
Anyone interested in gaining knowledge about Machine Learning can opt for this course. You don’t need to have expertise in the tech field or an advanced background to enrol in this course. Just a strong desire to learn and basic computer knowledge would be enough.
- College students with a mindset to get early exploration about AI and Machine Learning.
- Working professionals willing to upgrade their skills can choose this course.
- Complete beginners in programming can easily learn through this Machine Learning course.
- Career switchers who want to shift into the tech industry can enrol as we provide step-by-step guidance from the basics.
You can expect the following benefits by enrolling in the Best AI & Machine Learning classes in Pune
- Practically understand Machine Learning as we create a balance between theory and hands-on knowledge.
- This course will take you from the basics to the advanced level, whether you are a beginner or a seasoned professional.
- Learn industry-relevant tools and techniques that are used by top companies professionals.
- Boost your career by being eligible for in-demand roles such as Data Analyst, ML Engineer, and AI Specialist.
- Earn a certificate after completing the course to showcase your skills and attract potential employers.
This course precisely delivers valuable and in-demand Machine Learning skills that will open doors to successful career paths.
Jobs after Learning the Best AI and Machine Learning Training in Pune
Completing this online Machine Learning course in Pune will unlock doors to many well-paying job roles and exciting career paths. Various sectors’ companies are actively hiring Machine Learning-skilled professionals, such as finance, e-commerce, healthcare, and entertainment.
Top career paths to explore:
- Machine Learning Engineer
- Data Scientist
- AI/ML Developer
- Data Analyst
- Business Intelligence (BI) Analyst
- Research Analyst
You will not be limited to just the tech industry; Machine Learning skills are valued in industries where companies seek growth and innovation.
Our students are working in leading organizations
AI and Machine Learning Course in Pune FAQs
Basic understanding of any programming language, especially Python, can turn out to be helpful but not necessary. We will provide guidance on coding essentials needed for Machine Learning.
Yes, these online Machine Learning classes in Pune are designed to be beginner-friendly. We begin from the basics and gradually cover advanced topics, making it easy for beginners to learn.
Yes! You’ll work on real-world datasets and practical projects to understand how Machine Learning works in industries.
During this course, you will learn Python, Pandas, NumPy, Scikit-Learn, and basic concepts of data visualization using libraries like Matplotlib.
Yes, you will earn a certificate after completing the Best AI & Machine Learning training in Pune. This certificate will showcase your skills, and you can add it to your LinkedIn profile to attract employers.
Projects such as predicting house prices, customer segmentation, sales forecasting, and basic fraud detection models will be present in this Machine Learning course.
Yes, non-technical students can join. We focus on building concepts from the basics and explain everything in easy language.
You can explore job roles in data science, analytics, and AI development with Machine Learning skills. These practical skills are highly valued by employers.
This is a hands-on course, which means you will gain practical knowledge. We teach theoretical concepts where the primary focus is on practical approaches to solve real-world problems.
We provide dedicated support to answer your queries and help you move forward smoothly throughout your learning journey in this course.
