Data Science Courses
6,094 Learnerscourse
Introduction to Neural Networks with Python
4 hours
25 chaptersAdvanced
11 STUDYING NOW
Acquired skills: Neural Networks, Model Training and Evaluation, Data Preprocessing, Hyperparameter Tuning, Machine Learning with scikit-learn
course
Introduction to Machine Learning with Python
4 hours 32 chaptersIntermediate
19 STUDYING NOW
Acquired skills: Machine Learning with scikit-learn, Model Training and Evaluation, Hyperparameter Tuning
course
Introduction to NLP with Python
5 hours 29 chaptersAdvanced
1 STUDYING NOW
Acquired skills: Natural Language Processing, Natural Language Handling
course
Introduction to TensorFlow
3 hours 18 chaptersAdvanced
3 STUDYING NOW
Acquired skills: TensorFlow Basics, Neural Networks, Python Data Structures, Data Preprocessing
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Linear Regression with Python
2 hours 19 chaptersIntermediate
2 STUDYING NOW
Acquired skills: Linear Regression with Python, Model Training and Evaluation
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Classification with Python
3 hours 24 chaptersIntermediate
2 STUDYING NOW
Acquired skills: Python Programming, Python Classification Models, Logistic Regression, Data Preprocessing, Model Training and Evaluation, Hyperparameter Tuning
course
Cluster Analysis with Python
4 hours 34 chaptersIntermediate
4 STUDYING NOW
Acquired skills: Clustering fundamentals and algorithms , Handling missing and categorical data , Data normalization and distance metrics , K-Means: principles and cluster optimization , Hierarchical clustering and dendrograms , DBSCAN: noise handling and irregular shapes , Gaussian Mixture Models: probabilistic clustering
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Recurrent Neural Networks with Python
3 hours 22 chaptersIntermediate
1 STUDYING NOW
Acquired skills: Understanding RNNs, LSTMs, and GRUs, Implementing recurrent networks in PyTorch, Processing time series and sequential data, Applying RNNs to NLP tasks (sentiment analysis) , End-to-end model development and evaluation
course
Mathematics for Data Science
5 hours 51 chaptersBeginner
10 STUDYING NOW
Acquired skills: Functions & Sets, Series Analysis , Limits & Derivatives , Integrals , Gradient Descent , Vectors & Matrices , Linear Transformations , Matrix Decomposition , Probability Rules , Bayes' Theorem, Statistical Measures , Probability Distributions
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Data Preprocessing and Feature Engineering with Python
1 hour 12 chaptersBeginner
7 STUDYING NOW
Acquired skills: Data Cleaning , Missing Value Imputation , Outlier Detection , Feature Encoding , Feature Scaling , Data Transformation , Feature Engineering , Feature Selection , Pipeline Building
course
Explainable AI (XAI) Basics
1 hour 15 chaptersBeginner
1 STUDYING NOW
Acquired skills: Explainable AI Fundamentals, XAI Methods and Concepts, Ethical AI Principles, AI Transparency Awareness
course
Introduction to Reinforcement Learning with Python
6 hours 37 chaptersAdvanced
1 STUDYING NOW
Acquired skills: Reinforcement Learning Foundations, Multi-Armed Bandit Algorithms, Dynamic Programming Methods, Monte Carlo Techniques, Temporal-Difference Learning, Gymnasium Basics
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20+ hands-on Real-world projectsPersonalized study tracksUnlimited workspaces100+ Top-Rated coursesCompletion certificatesAI-Assistant in all courses20+ hands-on Real-world projectsPersonalized study tracksUnlimited workspaces1. | Introduction to Neural Networks with Python |  4 hours |  25 chapters |
2. | Introduction to Machine Learning with Python | 4 hours | 32 chapters |
3. | Introduction to NLP with Python | 5 hours | 29 chapters |
4. | Introduction to TensorFlow | 3 hours | 18 chapters |
5. | Linear Regression with Python | 2 hours | 19 chapters |
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