FreeCourseSite com Udemy AI Engineering Masterclass From Zero to AI Hero

FreeCourseSite com Udemy AI Engineering Masterclass From Zero to AI Hero

Name	[FreeCourseSite.com] Udemy - AI Engineering Masterclass From Zero to AI Hero	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	18.7 GB
Total Files	160
Last Seen	2025-07-18 01:09
Hash	BE93583A8B0917FF2F94FAB29EDAADAB349B4264

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/1 - Week 1 Python Programming Basics/
1 - Introduction to Week 1 Python Programming Basics.mp4	1.5 MB
2 - Day 1 Introduction to Python and Development Setup.mp4	202.7 MB
3 - Day 2 Control Flow in Python.mp4	153.5 MB
4 - Day 3 Functions and Modules.mp4	95.9 MB
5 - Day 4 Data Structures Lists Tuples Dictionaries Sets.mp4	161.4 MB
6 - Day 5 Working with Strings.mp4	179.8 MB
7 - Day 6 File Handling.mp4	119.0 MB
8 - Day 7 Pythonic Code and Project Work.mp4	505.5 MB
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/10 - Week 10 Convolutional Neural Networks CNNs/
73 - Introduction to Week 10 Convolutional Neural Networks CNNs.mp4	2.3 MB
74 - Day 1 Introduction to Convolutional Neural Networks.mp4	345.2 MB
75 - Day 2 Convolutional Layers and Filters.mp4	312.1 MB
76 - Day 3 Pooling Layers and Dimensionality Reduction.mp4	165.1 MB
77 - Day 4 Building CNN Architectures with Keras and TensorFlow.mp4	112.7 MB
78 - Day 5 Building CNN Architectures with PyTorch.mp4	243.2 MB
79 - Day 6 Regularization and Data Augmentation for CNNs.mp4	211.1 MB
80 - Day 7 CNN Project Image Classification on Fashion MNIST or CIFAR10.mp4	188.3 MB
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/11 - Week 11 Recurrent Neural Networks RNNs and Sequence Modeling/
81 - Introduction to Week 11 Recurrent Neural Networks RNNs and Sequence Modeling.mp4	2.4 MB
82 - Day 1 Introduction to Sequence Modeling and RNNs.mp4	395.5 MB
83 - Day 2 Understanding RNN Architecture and Backpropagation Through Time BPTT.mp4	248.7 MB
84 - Day 3 Long ShortTerm Memory LSTM Networks.mp4	130.9 MB
85 - Day 4 Gated Recurrent Units GRUs.mp4	60.5 MB
86 - Day 5 Text Preprocessing and Word Embeddings for RNNs.mp4	241.4 MB
87 - Day 6 SequencetoSequence Models and Applications.mp4	678.2 MB
88 - Day 7 RNN Project Text Generation or Sentiment Analysis.mp4	182.2 MB
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/12 - Week 12 Transformers and Attention Mechanisms/
89 - Introduction to Week 12 Transformers and Attention Mechanisms.mp4	2.3 MB
90 - Day 1 Introduction to Attention Mechanisms.mp4	87.3 MB
91 - Day 2 Introduction to Transformers Architecture.mp4	224.1 MB
92 - Day 3 SelfAttention and MultiHead Attention in Transformers.mp4	284.2 MB
93 - Day 4 Positional Encoding and FeedForward Networks.mp4	195.8 MB
94 - Day 5 HandsOn with PreTrained Transformers BERT and GPT.mp4	276.4 MB
95 - Day 6 Advanced Transformers BERT Variants and GPT3.mp4	282.3 MB
96 - Day 7 Transformer Project Text Summarization or Translation.mp4	258.6 MB
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/13 - Week 13 Transfer Learning and FineTuning/
100 - Day 3 FineTuning Techniques in Computer Vision.mp4	148.1 MB
101 - Day 4 Transfer Learning in NLP.mp4	240.7 MB
102 - Day 5 FineTuning Techniques in NLP.mp4	175.8 MB
103 - Day 6 Domain Adaptation and Transfer Learning Challenges.mp4	151.3 MB
104 - Day 7 Transfer Learning Project FineTuning for a Custom Task.mp4	257.6 MB
97 - Introduction to Week 13 Transfer Learning and FineTuning.mp4	1.9 MB
98 - Day 1 Introduction to Transfer Learning.mp4	195.4 MB
99 - Day 2 Transfer Learning in Computer Vision.mp4	278.7 MB
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/2 - Week 2 Data Science Essentials/
10 - Day 1 Introduction to NumPy for Numerical Computing.mp4	236.3 MB
11 - Day 2 Advanced NumPy Operations.mp4	100.3 MB
12 - Day 3 Introduction to Pandas for Data Manipulation.mp4	250.2 MB
13 - Day 4 Data Cleaning and Preparation with Pandas.mp4	126.7 MB
14 - Day 5 Data Aggregation and Grouping in Pandas.mp4	80.5 MB
15 - Day 6 Data Visualization with Matplotlib and Seaborn.mp4	373.8 MB
16 - Day 7 Exploratory Data Analysis EDA Project.mp4	274.4 MB
9 - Introduction to Week 2 Data Science Essentials.mp4	1.8 MB
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/3 - Week 3 Mathematics for Machine Learning/
17 - Introduction to Week 3 Mathematics for Machine Learning.mp4	1.9 MB
18 - Day 1 Linear Algebra Fundamentals.mp4	95.7 MB
19 - Day 2 Advanced Linear Algebra Concepts.mp4	104.5 MB
20 - Day 3 Calculus for Machine Learning Derivatives.mp4	82.5 MB
21 - Day 4 Calculus for Machine Learning Integrals and Optimization.mp4	82.3 MB
22 - Day 5 Probability Theory and Distributions.mp4	296.3 MB
23 - Day 6 Statistics Fundamentals.mp4	91.0 MB
24 - Day 7 MathDriven Mini Project Linear Regression from Scratch.mp4	75.6 MB
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/4 - Week 4 Probability and Statistics for Machine Learning/
25 - Introduction to Week 4 Probability and Statistics for Machine Learning.mp4	2.1 MB
26 - Day 1 Probability Theory and Random Variables.mp4	96.0 MB
27 - Day 2 Probability Distributions in Machine Learning.mp4	185.0 MB
28 - Day 3 Statistical Inference Estimation and Confidence Intervals.mp4	73.4 MB
29 - Day 4 Hypothesis Testing and PValues.mp4	98.1 MB
30 - Day 5 Types of Hypothesis Tests.mp4	103.7 MB
31 - Day 6 Correlation and Regression Analysis.mp4	97.0 MB
32 - Day 7 Statistical Analysis Project Analyzing RealWorld Data.mp4	350.9 MB
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/5 - Week 5 Introduction to Machine Learning/
33 - Introduction to Week 5 Introduction to Machine Learning.mp4	2.1 MB
34 - Day 1 Machine Learning Basics and Terminology.mp4	154.0 MB
35 - Day 2 Introduction to Supervised Learning and Regression Models.mp4	66.0 MB
36 - Day 3 Advanced Regression Models Polynomial Regression and Regularization.mp4	516.8 MB
37 - Day 4 Introduction to Classification and Logistic Regression.mp4	268.3 MB
38 - Day 5 Model Evaluation and CrossValidation.mp4	132.6 MB
39 - Day 6 kNearest Neighbors kNN Algorithm.mp4	106.9 MB
40 - Day 7 Supervised Learning Mini Project.mp4	173.0 MB
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/6 - Week 6 Feature Engineering and Model Evaluation/
41 - Introduction to Week 6 Feature Engineering and Model Evaluation.mp4	1.7 MB
42 - Day 1 Introduction to Feature Engineering.mp4	170.1 MB
43 - Day 2 Data Scaling and Normalization.mp4	190.0 MB
44 - Day 3 Encoding Categorical Variables.mp4	85.7 MB
45 - Day 4 Feature Selection Techniques.mp4	218.7 MB
46 - Day 5 Creating and Transforming Features.mp4	203.5 MB
47 - Day 6 Model Evaluation Techniques.mp4	89.9 MB
48 - Day 7 CrossValidation and Hyperparameter Tuning.mp4	270.1 MB
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/7 - Week 7 Advanced Machine Learning Algorithms/
49 - Introduction to Week 7 Advanced Machine Learning Algorithms.mp4	1.7 MB
50 - Day 1 Introduction to Ensemble Learning.mp4	89.4 MB
51 - Day 2 Bagging and Random Forests.mp4	178.8 MB
52 - Day 3 Boosting and Gradient Boosting.mp4	183.5 MB
53 - Day 4 Introduction to XGBoost.mp4	250.0 MB
54 - Day 5 LightGBM and CatBoost.mp4	271.3 MB
55 - Day 6 Handling Imbalanced Data.mp4	165.1 MB
56 - Day 7 Ensemble Learning Project Comparing Models on a Real Dataset.mp4	244.0 MB
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/8 - Week 8 Model Tuning and Optimization/
57 - Introduction to Week 8 Model Tuning and Optimization.mp4	2.5 MB
58 - Day 1 Introduction to Hyperparameter Tuning.mp4	160.2 MB
59 - Day 2 Grid Search and Random Search.mp4	161.1 MB
60 - Day 3 Advanced Hyperparameter Tuning with Bayesian Optimization.mp4	407.3 MB
61 - Day 4 Regularization Techniques for Model Optimization.mp4	201.2 MB
62 - Day 5 CrossValidation and Model Evaluation Techniques.mp4	146.5 MB
63 - Day 6 Automated Hyperparameter Tuning with GridSearchCV and RandomizedSearchCV.mp4	288.0 MB
64 - Day 7 Optimization Project Building and Tuning a Final Model.mp4	245.4 MB
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/9 - Week 9 Neural Networks and Deep Learning Fundamentals/
65 - Introduction to Week 9 Neural Networks and Deep Learning Fundamentals.mp4	2.2 MB
66 - Day 1 Introduction to Deep Learning and Neural Networks.mp4	177.1 MB
67 - Day 2 Forward Propagation and Activation Functions.mp4	180.8 MB
68 - Day 3 Loss Functions and Backpropagation.mp4	93.4 MB
69 - Day 4 Gradient Descent and Optimization Techniques.mp4	303.5 MB
70 - Day 5 Building Neural Networks with TensorFlow and Keras.mp4	244.1 MB
71 - Day 6 Building Neural Networks with PyTorch.mp4	409.6 MB
72 - Day 7 Neural Network Project Image Classification on CIFAR10.mp4	333.3 MB
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Total files 160