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Mastering Data Science: From Basics to Advanced Techniques

Master Data Science: Your Comprehensive Guide to Python, SQL, Machine Learning & Deep Learning! Explore step-by-step tutorials and projects, from coding fundamentals to advanced algorithms, with codebasics. Unlock your data-driven career today!

4.6 (4)
64 learners

What you'll learn

Understand the fundamentals of data science and its applications
Acquire skills in Python programming and data analysis using libraries like Pandas and NumPy
Develop machine learning models and understand key algorithms such as Linear Regression, Decision Trees, and Neural Networks
Use deep learning frameworks like TensorFlow and Keras to build and deploy neural network models

This course includes

  • 34.1 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 122 lessons • 34.1 hours of video

"Comprehensive Introduction to Data Science and Python Programming"
122 lessons • 34.1 hours
▶
  • What is Data Science? | Free Data Science Course | Data Science for Beginners | codebasics06:46
  • Data Science Roadmap 2023 | Learn Data Science Skills in 6 Months48:29
  • Business Math & Statistics Using Excel For Data Analysts and Data Scientists01:24:49
  • SQL Tutorial For Beginners | MySQL Tutorial01:26:09
  • 1. Install python on windows [Python 3 Programming Tutorials]03:52
  • 2. Variables in python [Python 3 Programming Tutorials]03:43
  • 3. Numbers [Python 3 Programming Tutorials]08:45
  • 4. Strings [Python 3 Programming Tutorials]07:12
  • 5. Lists [Python 3 Programming Tutorials]10:24
  • 6. Install PyCharm on Windows [Python 3 Programming Tutorials]06:33
  • 7. Debug Python code using PyCharm [Python 3 Programming Tutorials]09:39
  • 8. If Statement [Python 3 Programming Tutorials]13:18
  • 9. For loop [Python 3 Programming Tutorials]20:41
  • 10. Functions [Python 3 Programming Tutorials]16:10
  • 11. Dictionaries and Tuples [Python 3 Programming Tutorials]08:46
  • 12.1 - Install Python Module (using pip) [Python 3 Programming Tutorials]03:07
  • 12. Modules [Python 3 Programming Tutorials]11:02
  • 13. Working With JSON [Python 3 Programming Tutorials]08:41
  • 14. if __name__ == "__main__" [Python 3 Programming Tutorials]04:24
  • 15. Exception Handling [Python 3 Programming Tutorials]09:09
  • 16. Class and Objects [Python 3 Programming Tutorials]09:50
  • What is Jupyter Notebook? | Jupyter Notebook Tutorial in Python08:25
  • What is Anaconda? Install Anaconda On Windows.05:22
  • Jupyter Notebook Tutorial / Ipython Notebook Tutorial24:08
  • numpy tutorial - basic array operations13:48
  • Python Pandas Tutorial 1. What is Pandas python? Introduction and Installation09:23
  • Python Pandas Tutorial 2: Dataframe Basics20:58
  • Python Pandas Tutorial 3: Different Ways Of Creating DataFrame07:39
  • Python Pandas Tutorial 4: Read Write Excel CSV File27:03
  • Python Pandas Tutorial 5: Handle Missing Data: fillna, dropna, interpolate22:07
  • Python Pandas Tutorial 6. Handle Missing Data: replace function13:21
  • Python Pandas Tutorial 7. Group By (Split Apply Combine)10:34
  • Python Pandas Tutorial 8. Concat Dataframes15:13
  • Matplotlib Tutorial 1 - Introduction and Installation06:59
  • Matplotlib Tutorial 2 - format strings in plot function06:17
  • Matplotlib Tutorial 3 - Axes labels, Legend, Grid06:58
  • Matplotlib Tutorial 4 - Bar Chart08:45
  • Matplotlib Tutorial 5 - Histograms08:18
  • Matplotlib Tutorial 6 - Pie Chart06:36
  • Machine Learning Tutorial Python -1: What is Machine Learning?06:50
  • Machine Learning Tutorial Python - 2: Linear Regression Single Variable15:14
  • Machine Learning Tutorial Python - 3: Linear Regression Multiple Variables14:08
  • Machine Learning Tutorial Python - 4: Gradient Descent and Cost Function28:25
  • Machine Learning Tutorial Python - 5: Save Model Using Joblib And Pickle08:21
  • Machine Learning Tutorial Python - 6: Dummy Variables & One Hot Encoding21:34
  • Machine Learning Tutorial Python - 7: Training and Testing Data06:33
  • Machine Learning Tutorial Python - 8: Logistic Regression (Binary Classification)19:19
  • Machine Learning Tutorial Python - 8 Logistic Regression (Multiclass Classification)15:43
  • Machine Learning Tutorial Python - 9 Decision Tree14:45
  • Machine Learning Tutorial Python - 10 Support Vector Machine (SVM)23:22
  • Machine Learning Tutorial Python - 11 Random Forest12:48
  • Machine Learning Tutorial Python 12 - K Fold Cross Validation25:20
  • Machine Learning Tutorial Python - 13: K Means Clustering Algorithm25:15
  • Machine Learning Tutorial Python - 14: Naive Bayes Classifier Algorithm Part 113:37
  • Machine Learning Tutorial Python - 15: Naive Bayes Classifier Algorithm Part 211:28
  • Machine Learning Tutorial Python - 16: Hyper parameter Tuning (GridSearchCV)16:29
  • Machine Learning Tutorial Python - 17: L1 and L2 Regularization | Lasso, Ridge Regression19:21
  • Machine Learning & Data Science Project - 1 : Introduction (Real Estate Price Prediction Project)02:11
  • Machine Learning & Data Science Project - 2 : Data Cleaning (Real Estate Price Prediction Project)15:21
  • Machine Learning & Data Science Project - 3 : Feature Engineering (Real Estate Price Prediction)08:26
  • Machine Learning & Data Science Project - 4 : Outlier Removal (Real Estate Price Prediction Project)19:30
  • Machine Learning & Data Science Project - 5 : Model Building (Real Estate Price Prediction Project)19:11
  • Machine Learning & Data Science Project - 6 : Python Flask Server (Real Estate Price Prediction)21:13
  • Machine Learning & Data Science Project - 7 : Website or UI (Real Estate Price Prediction Project)13:21
  • Deploy machine learning model to production AWS (Amazon EC2 instance)28:38
  • Data Analyst vs Data Engineer vs Data Scientist10:51
  • Data Science & Machine Learning Project - Part 1 Introduction | Image Classification04:42
  • Data Science & Machine Learning Project - Part 2 Data Collection | Image Classification05:37
  • Data Science & Machine Learning Project - Part 3 Data Cleaning | Image Classification40:44
  • Data Science & Machine Learning Project - Part 4 Feature Engineering | Image Classification18:23
  • Data Science & Machine Learning Project - Part 5 Training a Model | Image Classification20:00
  • Data Science & Machine Learning Project - Part 6 Flask Server | Image Classification36:16
  • Data Science & Machine Learning Project - Part 7 Build Website | Image Classification38:14
  • Data Science & Machine Learning Project - Part 8 Deployment & Exercise | Image Classification05:16
  • Introduction | Deep Learning Tutorial 1 (Tensorflow Tutorial, Keras & Python)03:39
  • Why deep learning is becoming so popular? | Deep Learning Tutorial 2 (Tensorflow2.0, Keras & Python)05:24
  • What is a neuron? | Deep Learning Tutorial 3 (Tensorflow Tutorial, Keras & Python)16:48
  • Neural Network Simply Explained | Deep Learning Tutorial 4 (Tensorflow2.0, Keras & Python)11:00
  • Install tensorflow 2.0 | Deep Learning Tutorial 5 (Tensorflow Tutorial, Keras & Python)02:37
  • Pytorch vs Tensorflow vs Keras | Deep Learning Tutorial 6 (Tensorflow Tutorial, Keras & Python)02:16
  • Neural Network For Handwritten Digits Classification | Deep Learning Tutorial 7 (Tensorflow2.0)36:39
  • Activation Functions | Deep Learning Tutorial 8 (Tensorflow Tutorial, Keras & Python)16:29
  • Derivatives | Deep Learning Tutorial 9 (Tensorflow Tutorial, Keras & Python)12:35
  • Matrix Basics | Deep Learning Tutorial 10 (Tensorflow Tutorial, Keras & Python)11:41
  • Loss or Cost Function | Deep Learning Tutorial 11 (Tensorflow Tutorial, Keras & Python)24:37
  • Gradient Descent For Neural Network | Deep Learning Tutorial 12 (Tensorflow2.0, Keras & Python)41:34
  • Implement Neural Network In Python | Deep Learning Tutorial 13 (Tensorflow2.0, Keras & Python)13:23
  • Stochastic Gradient Descent vs Batch Gradient Descent vs Mini Batch Gradient Descent |DL Tutorial 1436:47
  • Chain Rule | Deep Learning Tutorial 15 (Tensorflow2.0, Keras & Python)14:05
  • Tensorboard Introduction | Deep Learning Tutorial 16 (Tensorflow2.0, Keras & Python)14:56
  • GPU bench-marking with image classification | Deep Learning Tutorial 17 (Tensorflow2.0, Python)23:58
  • Customer churn prediction using ANN | Deep Learning Tutorial 18 (Tensorflow2.0, Keras & Python)40:41
  • Precision, Recall, F1 score, True Positive|Deep Learning Tutorial 19 (Tensorflow2.0, Keras & Python)11:45
  • Handling imbalanced dataset in machine learning | Deep Learning Tutorial 21 (Tensorflow2.0 & Python)38:26
  • Applications of computer vision | Deep Learning Tutorial 22 (Tensorflow2.0, Keras & Python)09:44
  • Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)23:54
  • Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python)28:11
  • Convolution padding and stride | Deep Learning Tutorial 25 (Tensorflow2.0, Keras & Python)06:35
  • Data augmentation to address overfitting | Deep Learning Tutorial 26 (Tensorflow, Keras & Python)31:32
  • Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python)25:54
  • Image classification vs Object detection vs Image Segmentation | Deep Learning Tutorial 2802:32
  • Popular datasets for computer vision: ImageNet, Coco and Google Open images | Deep Learning 2913:02
  • Sliding Window Object Detection | Deep Learning Tutorial 30 (Tensorflow, Keras & Python)04:57
  • What is YOLO algorithm? | Deep Learning Tutorial 31 (Tensorflow, Keras & Python)16:04
  • Object detection using YOLO v4 and pre trained model | Deep Learning Tutorial 32 (Tensorflow)14:53
  • What is Recurrent Neural Network (RNN)? Deep Learning Tutorial 33 (Tensorflow, Keras & Python)15:59
  • Types of RNN | Recurrent Neural Network Types | Deep Learning Tutorial 34 (Tensorflow & Python)03:43
  • Vanishing and exploding gradients | Deep Learning Tutorial 35 (Tensorflow, Keras & Python)09:52
  • Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)14:37
  • Simple Explanation of GRU (Gated Recurrent Units) | Deep Learning Tutorial 37 (Tensorflow & Python)08:14
  • Bidirectional RNN | Deep Learning Tutorial 38 (Tensorflow, Keras & Python)05:50
  • Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python)11:32
  • Word embedding using keras embedding layer | Deep Learning Tutorial 40 (Tensorflow, Keras & Python)21:34
  • What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python)18:27
  • Word2Vec Part 2 | Implement word2vec in gensim | | Deep Learning Tutorial 42 with Python18:40
  • Distributed Training On NVIDIA DGX Station A100 | Deep Learning Tutorial 43 (Tensorflow & Python)14:16
  • Tensorflow Input Pipeline | tf Dataset | Deep Learning Tutorial 44 (Tensorflow, Keras & Python)33:19
  • Optimize Tensorflow Pipeline Performance: prefetch & cache | Deep Learning Tutorial 45 (Tensorflow)26:15
  • What is BERT? | Deep Learning Tutorial 46 (Tensorflow, Keras & Python)23:03
  • Text Classification Using BERT & Tensorflow | Deep Learning Tutorial 47 (Tensorflow, Keras & Python)18:44
  • tf serving tutorial | tensorflow serving tutorial | Deep Learning Tutorial 48 (Tensorflow, Python)19:51
  • Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)15:34

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