AI Enginner (2026) Complete Course GEN AI Deep Machine LLM

[0dayddl]

12.6 GB | 13min 12s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English


Files Included :

1 1 1 Welcome to the Full Stack AI Engineer Master Program.mp4 (42.76 MB)
2 1 2 Who Is a Full Stack AI Engineer in 2026.mp4 (59.21 MB)
3 1 3 How This Course Is Structured End to End.mp4 (53.04 MB)
4 1 4 Tools Stack & Skills You'll Use Throughout.mp4 (51.03 MB)
5 1 5 How to Stay Consistent & Finish Strong.mp4 (50.56 MB)
6 2 1 Python Refresher for AI Engineers.mp4 (69.32 MB)
7 2 2 NumPy for Numerical Computing.mp4 (89.21 MB)
8 2 3 Data Handling with Pandas.mp4 (91.06 MB)
9 2 4 Writing Clean Modular ML Code.mp4 (93.25 MB)
10 2 5 Hands On Python Warm Up Lab.mp4 (69.62 MB)
11 3 1 Understanding Dataset Structure.mp4 (85.65 MB)
12 3 2 Missing Values Noise & Outliers.mp4 (84.18 MB)
13 3 3 Visualizing Data with Matplotlib.mp4 (94.25 MB)
14 3 4 Feature Relationships & Correlations.mp4 (93.18 MB)
15 3 5 Hands On EDA Mini Project.mp4 (87.14 MB)
16 4 1 What Is Machine Learning.mp4 (87.01 MB)
17 4 2 Supervised vs Unsupervised Learning.mp4 (104.72 MB)
18 4 3 Regression vs Classification Problems.mp4 (86.72 MB)
19 4 4 Train Validation Test Splits.mp4 (92.86 MB)
20 4 5 End to End ML Workflow.mp4 (145.67 MB)
21 5 1 Linear Regression Intuition.mp4 (142.3 MB)
22 5 2 Linear Regression Math (Simplified).mp4 (137.4 MB)
23 5 3 Implementing Linear Regression in Python.mp4 (145.52 MB)
24 5 4 Model Evaluation MSE RMSE & R².mp4 (125.49 MB)
25 5 5 Bias-Variance Tradeoff.mp4 (115.83 MB)
26 5 6 Mini Project Continuous Value Prediction.mp4 (137.35 MB)
27 6 1 Logistic Regression Explained.mp4 (140.47 MB)
28 6 2 Implementing Logistic Regression.mp4 (152.6 MB)
29 6 3 K Nearest Neighbors (KNN).mp4 (152.84 MB)
30 6 4 Decision Trees & Split Logic.mp4 (148.33 MB)
31 6 5 Classification Metrics Deep Dive.mp4 (171.71 MB)
32 6 6 Mini Project Binary Classification System.mp4 (180.54 MB)
33 7 1 Why Single Models Break.mp4 (149.86 MB)
34 7 2 Random Forests Explained.mp4 (180.04 MB)
35 7 3 Gradient Boosting Intuition.mp4 (175.68 MB)
36 7 4 Feature Importance & Interpretability.mp4 (188.62 MB)
37 7 5 Hands On Boosting Model Performance.mp4 (185.71 MB)
38 8 1 Understanding Unsupervised Learning.mp4 (141.43 MB)
39 8 2 K Means Clustering.mp4 (147.35 MB)
40 8 3 Choosing Optimal Number of Clusters.mp4 (142.78 MB)
41 8 4 Dimensionality Reduction with PCA.mp4 (152.99 MB)
42 8 5 Industry Use Cases of Clustering.mp4 (167.83 MB)
43 9 1 Feature Scaling & Normalization.mp4 (91.68 MB)
44 9 2 Encoding Categorical Variables.mp4 (115 MB)
45 9 3 Feature Selection Strategies.mp4 (110.42 MB)
46 9 4 Cross Validation Explained.mp4 (99.53 MB)
47 9 5 Hyperparameter Tuning (Grid & Random Search).mp4 (108.1 MB)
48 10 1 Building ML Pipelines.mp4 (97.83 MB)
49 10 2 Preventing Data Leakage.mp4 (99.81 MB)
50 10 3 Reproducibility in Machine Learning.mp4 (95.57 MB)
51 10 4 Common ML Mistakes to Avoid.mp4 (119.72 MB)
52 11 1 What Is Deep Learning & Why It Matters.mp4 (73.55 MB)
53 11 2 Machine Learning vs Deep Learning.mp4 (69.54 MB)
54 11 3 Deep Learning Use Cases in Industry.mp4 (72.65 MB)
55 11 4 Deep Learning Roadmap for AI Engineers.mp4 (90.92 MB)
56 11 5 Tools & Frameworks (PyTorch TensorFlow).mp4 (102.22 MB)
57 12 1 Biological Inspiration of Neural Networks.mp4 (128.97 MB)
58 12 2 Artificial Neurons & Perceptrons.mp4 (108.15 MB)
59 12 3 Layers Weights & Biases.mp4 (95.97 MB)
60 12 4 Forward Propagation Explained.mp4 (107.58 MB)
61 12 5 Hands On Neural Network from Scratch.mp4 (114.3 MB)
62 13 1 Why Activation Functions Matter.mp4 (106.44 MB)
63 13 2 Sigmoid Tanh ReLU & Variants.mp4 (106.64 MB)
64 13 3 Choosing the Right Activation.mp4 (89.95 MB)
65 13 4 Loss Functions for Regression & Classification.mp4 (87.93 MB)
66 13 5 Hands On Visualizing Activations & Loss.mp4 (80.45 MB)
67 14 1 Gradient Descent Intuition.mp4 (87.48 MB)
68 14 2 Backpropagation (Simplified).mp4 (112.38 MB)
69 14 3 Learning Rate & Convergence.mp4 (87.9 MB)
70 14 4 Optimizers SGD Momentum Adam.mp4 (99.91 MB)
71 15 1 Bias-Variance in Deep Learning.mp4 (59.71 MB)
72 15 2 Overfitting in Neural Networks.mp4 (81.57 MB)
73 15 3 L1 & L2 Regularization.mp4 (84.39 MB)
74 15 4 Dropout & Batch Normalization.mp4 (85.91 MB)
75 16 1 Tensors & Computation Graphs.mp4 (73.72 MB)
76 16 2 Building Networks Using Modules.mp4 (68.42 MB)
77 16 3 Training Loops & Evaluation.mp4 (84.17 MB)
78 16 4 GPU Acceleration Basics.mp4 (74.81 MB)
79 17 1 Why CNNs Beat Dense Networks.mp4 (80.77 MB)
80 17 2 Convolutions Filters & Feature Maps.mp4 (69.2 MB)
81 17 3 Pooling Layers Explained.mp4 (70.76 MB)
82 17 4 CNN Architecture Walkthrough.mp4 (77.27 MB)
83 18 1 Why Sequential Data Is Different.mp4 (75.48 MB)
84 18 2 Recurrent Neural Networks (RNNs).mp4 (82.02 MB)
85 18 3 LSTM & GRU Intuition.mp4 (68.52 MB)
86 18 4 Use Cases Time Series & Text.mp4 (66.64 MB)
87 19 1 Weight Initialization Strategies.mp4 (92.85 MB)
88 19 2 Debugging Deep Learning Models.mp4 (88.69 MB)
89 19 3 Monitoring Training & Validation Curves.mp4 (97.35 MB)
90 19 4 Reproducibility in Deep Learning.mp4 (98.88 MB)
91 19 5 Saving Loading & Versioning Models.mp4 (80.63 MB)
92 20 1 What Is Generative AI.mp4 (94.49 MB)
93 20 2 Evolution of Generative Models.mp4 (101.72 MB)
94 20 3 Generative AI Landscape.mp4 (111.2 MB)
95 21 1 Anatomy of Transformers.mp4 (99.01 MB)
96 21 2 Tokens Embeddings & Context Windows.mp4 (98.26 MB)
97 21 3 How LLMs Are Trained.mp4 (114.78 MB)
98 22 1 Popular LLM Families.mp4 (124.54 MB)
99 22 2 LLM Capabilities & Limitations.mp4 (104.56 MB)
100 22 3 Using LLM APIs.mp4 (95.96 MB)
101 23 1 Prompt Design Fundamentals.mp4 (93.08 MB)
102 23 2 Advanced Prompting Techniques.mp4 (116.76 MB)
103 23 3 Prompt Robustness & Safety.mp4 (103.76 MB)
104 24 1 What Are Embeddings.mp4 (107.9 MB)
105 24 2 Building Semantic Search Pipelines.mp4 (112.98 MB)
106 24 3 Vector Databases.mp4 (121.53 MB)
107 25 1 Why RAG is Needed.mp4 (100.14 MB)
108 25 2 RAG Architecture.mp4 (110.72 MB)
109 25 3 Advanced RAG Techniques.mp4 (89.81 MB)
110 26 1 Tool Using LLMs.mp4 (105.03 MB)
111 26 2 Designing Tools for LLMs.mp4 (91.88 MB)
112 26 3 Multi Step Reasoning with Tools.mp4 (93.8 MB)
113 27 1 What Are AI Agents.mp4 (102.41 MB)
114 27 2 Agent Architectures.mp4 (107.74 MB)
115 27 3 Building Practical Agents.mp4 (107.43 MB)
116 28 1 Backend Architecture for LLM Apps.mp4 (112.91 MB)
117 28 2 Frontend ? LLM Integration.mp4 (108.94 MB)
118 28 3 State Memory & Context Management.mp4 (116.09 MB)
119 29 1 Evaluating LLM Outputs.mp4 (106.78 MB)
120 29 2 Cost Optimization.mp4 (112.4 MB)
121 29 3 Latency & Scaling Considerations.mp4 (114.66 MB)
122 30 1 Ethical Considerations in Generative AI.mp4 (88.79 MB)
123 30 2 Security Risks.mp4 (93.87 MB)
124 30 3 Guardrails & Governance.mp4 (104.18 MB)

]
Screenshot

DDownload

Contenido oculto. Ha de estar registrado, y pulsar el botón "Gracias" para visualizar sus enlaces de descarga.
Si trás registrarse todavía no visualiza el botón de "gracias", pulse la tecla F5, para refrescar la página.

RapidGator

Contenido oculto. Ha de estar registrado, y pulsar el botón "Gracias" para visualizar sus enlaces de descarga.
Si trás registrarse todavía no visualiza el botón de "gracias", pulse la tecla F5, para refrescar la página.

NitroFlare

Contenido oculto. Ha de estar registrado, y pulsar el botón "Gracias" para visualizar sus enlaces de descarga.
Si trás registrarse todavía no visualiza el botón de "gracias", pulse la tecla F5, para refrescar la página.