6 Weeks Python with ML
- (416 Reviews)
Master Python for Machine Learning with hands-on training. Learn data preprocessing, algorithms, and model building to excel in AI-driven applications and projects.
Prepare for tech jobs with Python & ML
Efficient Problem-Solving Skills
C++ DSA improves logic, problem-solving, and coding skills for complex challenges.
High Performance and Speed
C++ offers fast execution, memory efficiency, ideal for competitive programming and system applications.
Essential for Coding Interviews
Top tech companies assess C++ DSA skills in interviews, essential for securing high-paying jobs.
Foundation for Advanced Technologies
Mastering C++ DSA builds a strong foundation for machine learning and development.
Master Skills with Detailed Curriculum
- Overview of Python and its applications in ML
- Setting up the development environment (Jupyter Notebook, Google Colab, Anaconda)
- Python basics: data types, loops, functions, and object-oriented programming
- NumPy and Pandas for data manipulation
- Handling missing values and data cleaning
- Feature engineering and selection techniques
- Data normalization and standardization
- Exploratory Data Analysis (EDA) with Matplotlib and Seaborn
- Introduction to supervised learning
- Linear Regression and Logistic Regression
- Decision Trees and Random Forest
- Support Vector Machines (SVM) and K-Nearest Neighbors (KNN)
- Introduction to unsupervised learning
- Clustering techniques (K-Means, DBSCAN, Hierarchical Clustering)
- Principal Component Analysis (PCA) for dimensionality reduction
- Association Rule Learning (Apriori, Eclat)
- Introduction to Neural Networks and Perceptrons
- Building deep learning models with TensorFlow and Keras
- Convolutional Neural Networks (CNN) for image classification
- Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)
- Text preprocessing (Tokenization, Lemmatization, Stemming)
- Sentiment analysis with machine learning models
- Named Entity Recognition (NER)
- Implementing Transformers and BERT models
- Performance metrics (Accuracy, Precision, Recall, F1-Score)
- Cross-validation and hyperparameter tuning (Grid Search, Random Search)
- Overfitting vs. Underfitting and model regularization techniques
- Bias-variance tradeoff and improving model accuracy
- Introduction to time series analysis
- Moving averages and exponential smoothing
- ARIMA and SARIMA models for forecasting
- Using LSTMs for time series predictions
- Introduction to big data and distributed computing
- ML model training with Apache Spark (MLlib)
- Handling large datasets efficiently
- Cloud-based ML with AWS, Google Cloud, and Azure
- Saving and loading trained models
- Deploying ML models using Flask and FastAPI
- Introduction to Docker and Kubernetes for ML applications
- CI/CD pipelines for machine learning
- Fraud detection system using ML
- Recommendation systems (E-commerce, Movie Recommendations)
- Image classification and object detection
- Final project: end-to-end ML model development and deployment
Summer Training Enquiry Form
What placement assistance will you receive?
Free Placement Prep Training
Learn how to build your resume, make great applications, and ace your interviews.
Curated Internships & Jobs
Get internships and fresher jobs as per your preference in your inbox.
Get highlighted on Bsates Edtech
Top performers will be highlighted in their internship & job applications.
How will your training work?
Learn Concepts
Go through training modules to learn and grasp essential concepts effectively.
Test Yourself
Test your knowledge through quizzes & module tests at regular intervals.
Hands-on Practice
Work on assignments and project. Use our in-browser IDE for coding practice.
1:1 Doubt Solving
Get your doubts solved by experts through Q&A forum within 24 hours.
Take Final Exam
Successfully complete your training by preparing for and taking the final exam.
Get Certified
Earn your Python with ML certification after successfully completing the training.
Most Popular Questions About Our Online Courses
This course teaches Python programming and Machine Learning fundamentals, covering data preprocessing, algorithms, deep learning, and model deployment for real-world applications.
Anyone interested in AI, data science, or ML, including students, professionals, and beginners with basic programming knowledge.
Basic Python knowledge is helpful but not mandatory, as the course covers Python fundamentals before diving into ML concepts.
The course includes Python basics, data preprocessing, supervised and unsupervised learning, deep learning, NLP, time series analysis, and model deployment.
The course typically lasts 6 to 12 weeks, depending on learning pace and practice.
Yes, you’ll earn a Python with ML certification upon successful completion, which can enhance your resume.
Yes, the training includes real-world projects, including image classification, recommendation systems, and time series forecasting.
It equips you with in-demand ML skills, helping you land jobs in AI, data science, and software development.
You can register online through the course provider’s website and start learning immediately.