24.27 GB | 43min 9s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English
Files Included :
3 Introduction to Week 1 Python Programming Basics.mp4 (3.58 MB)
4 Day 1 Introduction to Python and Development Setup.mp4 (195.94 MB)
5 Day 2 Control Flow in Python.mp4 (336.68 MB)
6 Day 3 Functions and Modules.mp4 (209.08 MB)
7 Day 4 Data Structures (Lists Tuples Dictionaries Sets).mp4 (303.31 MB)
8 Day 5 Working with Strings.mp4 (231.63 MB)
9 Day 6 File Handling.mp4 (226.02 MB)
10 Day 7 Pythonic Code and Project Work.mp4 (473.68 MB)
11 Introduction to Week 2 Data Science Essentials.mp4 (4.62 MB)
12 Day 1 Introduction to NumPy for Numerical Computing.mp4 (250.48 MB)
13 Day 2 Advanced NumPy Operations.mp4 (227.97 MB)
14 Day 3 Introduction to Pandas for Data Manipulation.mp4 (233.12 MB)
15 Day 4 Data Cleaning and Preparation with Pandas.mp4 (238.64 MB)
16 Day 5 Data Aggregation and Grouping in Pandas.mp4 (150.09 MB)
17 Day 6 Data Visualization with Matplotlib and Seaborn.mp4 (347.31 MB)
18 Day 7 Exploratory Data Analysis (EDA) Project.mp4 (257 MB)
19 Introduction to Week 3 Mathematics for Machine Learning.mp4 (4.7 MB)
20 Day 1 Linear Algebra Fundamentals.mp4 (223.73 MB)
21 Day 2 Advanced Linear Algebra Concepts.mp4 (205.72 MB)
22 Day 3 Calculus for Machine Learning (Derivatives).mp4 (188.74 MB)
23 Day 4 Calculus for Machine Learning (Integrals and Optimization).mp4 (157.56 MB)
24 Day 5 Probability Theory and Distributions.mp4 (279 MB)
25 Day 6 Statistics Fundamentals.mp4 (210.56 MB)
26 Day 7 Math Driven Mini Project - Linear Regression from Scratch.mp4 (172.5 MB)
27 Introduction to Week 4 Probability and Statistics for Machine Learning.mp4 (5.26 MB)
28 Day 1 Probability Theory and Random Variables.mp4 (190.15 MB)
29 Day 2 Probability Distributions in Machine Learning.mp4 (175.65 MB)
30 Day 3 Statistical Inference Estimation and Confidence Intervals.mp4 (174.63 MB)
31 Day 4 Hypothesis Testing and P Values.mp4 (106.07 MB)
32 Day 5 Types of Hypothesis Tests.mp4 (203.54 MB)
33 Day 6 Correlation and Regression Analysis.mp4 (192.43 MB)
34 Day 7 Statistical Analysis Project - Analyzing Real World Data.mp4 (319.98 MB)
35 Introduction to Week 5 Introduction to Machine Learning.mp4 (5.19 MB)
36 Day 1 Machine Learning Basics and Terminology.mp4 (146.73 MB)
37 Day 2 Introduction to Supervised Learning and Regression Models.mp4 (152.92 MB)
38 Day 3 Advanced Regression Models - Polynomial Regression and Regularization.mp4 (473.69 MB)
39 Day 4 Introduction to Classification and Logistic Regression.mp4 (283.1 MB)
40 Day 5 Model Evaluation and Cross Validation.mp4 (173.52 MB)
41 Day 6 k Nearest Neighbors (k NN) Algorithm.mp4 (181.39 MB)
42 Day 7 Supervised Learning Mini Project.mp4 (349.78 MB)
43 Introduction to Week 6 Feature Engineering and Model Evaluation.mp4 (4.3 MB)
44 Day 1 Introduction to Feature Engineering.mp4 (159.48 MB)
45 Day 2 Data Scaling and Normalization.mp4 (199.95 MB)
46 Day 3 Encoding Categorical Variables.mp4 (201.34 MB)
47 Day 4 Feature Selection Techniques.mp4 (201.45 MB)
48 Day 5 Creating and Transforming Features.mp4 (214.73 MB)
49 Day 6 Model Evaluation Techniques.mp4 (181.36 MB)
50 Day 7 Cross Validation and Hyperparameter Tuning.mp4 (249.15 MB)
51 Introduction to Week 7 Advanced Machine Learning Algorithms.mp4 (4.08 MB)
52 Day 1 Introduction to Ensemble Learning.mp4 (178.44 MB)
53 Day 2 Bagging and Random Forests.mp4 (165.51 MB)
54 Day 3 Boosting and Gradient Boosting.mp4 (193.6 MB)
55 Day 4 Introduction to XGBoost.mp4 (233 MB)
56 Day 5 LightGBM and CatBoost.mp4 (252.4 MB)
57 Day 6 Handling Imbalanced Data.mp4 (215.63 MB)
58 Day 7 Ensemble Learning Project - Comparing Models on a Real Dataset.mp4 (317.78 MB)
59 Introduction to Week 8 Model Tuning and Optimization.mp4 (6.02 MB)
60 Day 1 Introduction to Hyperparameter Tuning.mp4 (169.06 MB)
61 Day 2 Grid Search and Random Search.mp4 (213.52 MB)
62 Day 3 Advanced Hyperparameter Tuning with Bayesian Optimization.mp4 (373.39 MB)
63 Day 4 Regularization Techniques for Model Optimization.mp4 (181.34 MB)
64 Day 5 Cross Validation and Model Evaluation Techniques.mp4 (154.66 MB)
65 Day 6 Automated Hyperparameter Tuning with GridSearchCV and RandomizedSearchCV.mp4 (262.83 MB)
66 Day 7 Optimization Project - Building and Tuning a Final Model.mp4 (319.64 MB)
107 How AI Engineering Changed.mp4 (75.69 MB)
108 LLM APIs vs Open Source Models (OpenAI Anthropic Llama).mp4 (105.03 MB)
109 Prompt Engineering vs Prompt Programming.mp4 (112.11 MB)
110 Retrieval Augmented Generation (RAG) Architectures.mp4 (89.22 MB)
111 Vector Databases (FAISS Pinecone Weaviate).mp4 (73.7 MB)
112 Tool Calling & Function Calling.mp4 (66.1 MB)
113 Mini Project Build a Production Grade RAG App.mp4 (77.4 MB)
114 What Is an AI Agent (vs LLM App).mp4 (68.29 MB)
115 Agent Loops Plan → Act → Observe → Reflect.mp4 (61.09 MB)
116 ReAct Chain of Thought Tree of Thoughts.mp4 (76.56 MB)
117 Memory in Agents (Short term & Long term).mp4 (59.62 MB)
118 Multi Agent Systems & Orchestration.mp4 (85.97 MB)
119 Guardrails Safety & Failure Modes.mp4 (79.06 MB)
120 Capstone Build an Autonomous AI Agent.mp4 (71.41 MB)
121 From Notebook to Production.mp4 (61.66 MB)
122 Model Packaging & APIs (FastAPI Flask).mp4 (71.16 MB)
123 CI CD for ML Systems.mp4 (79.43 MB)
124 Model Monitoring & Drift Detection.mp4 (70.12 MB)
125 LLM Evals & Quality Metrics.mp4 (80.8 MB)
126 Cost Optimization & Latency Tradeoffs.mp4 (72.17 MB)
127 Project Deploy & Monitor an AI System.mp4 (61.37 MB)
128 What Recruiters Actually Look For.mp4 (63.92 MB)
129 Structuring AI Projects for Impact.mp4 (56.57 MB)
130 Writing README Files That Get Interviews.mp4 (64.61 MB)
131 Turning Projects into Case Studies.mp4 (60.05 MB)
132 Open Source Contributions Strategy.mp4 (71.11 MB)
133 Personal Website for AI Engineers.mp4 (58.25 MB)
134 Portfolio Review Checklist.mp4 (62.35 MB)
135 AI Engineer Interview Formats (FAANG Startups Enterprises).mp4 (101.07 MB)
136 Python Coding Interviews (Patterns & Pitfalls).mp4 (65.82 MB)
137 ML Theory Interview Questions.mp4 (77.02 MB)
138 Deep Learning & Transformers Interviews.mp4 (67.57 MB)
139 System Design for AI Systems.mp4 (59.8 MB)
140 Take Home Assignments How to Win.mp4 (65.15 MB)
141 Mock Interviews (Technical + Behavioral).mp4 (59.59 MB)
142 AI Engineer Resume That Passes ATS.mp4 (69.81 MB)
143 Writing Impact Driven Bullet Points.mp4 (56.21 MB)
144 LinkedIn & Personal Branding for AI Engineers.mp4 (58.63 MB)
145 Networking Strategies That Actually Work.mp4 (61.1 MB)
146 How to Apply Strategically (Not 500 Applications).mp4 (58.3 MB)
147 Salary Negotiation for AI Roles.mp4 (69.89 MB)
148 90 Day Plan for Your First AI Engineer Role.mp4 (79.23 MB)
1 Introduction to How to Land an AI Engineer Job in 2026.mp4 (83.25 MB)
68 Day 1 Introduction to Deep Learning and Neural Networks.mp4 (168.26 MB)
69 Day 2 Forward Propagation and Activation Functions.mp4 (169.24 MB)
70 Day 3 Loss Functions and Backpropagation.mp4 (181.86 MB)
71 Day 4 Gradient Descent and Optimization Techniques.mp4 (279.44 MB)
72 Day 5 Building Neural Networks with TensorFlow and Keras.mp4 (230.77 MB)
73 Day 6 Building Neural Networks with PyTorch.mp4 (372.89 MB)
74 Day 7 Neural Network Project - Image Classification on CIFAR 10.mp4 (305.58 MB)
75 Introduction to Week 10 Convolutional Neural Networks (CNNs).mp4 (6.45 MB)
76 Day 1 Introduction to Convolutional Neural Networks.mp4 (324.06 MB)
77 Day 2 Convolutional Layers and Filters.mp4 (292.89 MB)
78 Day 3 Pooling Layers and Dimensionality Reduction.mp4 (323.38 MB)
79 Day 4 Building CNN Architectures with Keras and TensorFlow.mp4 (214.6 MB)
80 Day 5 Building CNN Architectures with PyTorch.mp4 (322.29 MB)
81 Day 6 Regularization and Data Augmentation for CNNs.mp4 (222.42 MB)
82 Day 7 CNN Project - Image Classification on Fashion MNIST or CIFAR 10.mp4 (385.86 MB)
84 Day 1 Introduction to Sequence Modeling and RNNs.mp4 (415.3 MB)
86 Day 3 Long Short Term Memory (LSTM) Networks.mp4 (170.7 MB)
87 Day 4 Gated Recurrent Units (GRUs).mp4 (80.17 MB)
88 Day 5 Text Preprocessing and Word Embeddings for RNNs.mp4 (317.5 MB)
89 Day 6 Sequence to Sequence Models and Applications.mp4 (616.33 MB)
91 Introduction to Week 12 Transformers and Attention Mechanisms.mp4 (5.76 MB)
92 Day 1 Introduction to Attention Mechanisms.mp4 (168.69 MB)
93 Day 2 Introduction to Transformers Architecture.mp4 (211.81 MB)
94 Day 3 Self Attention and Multi Head Attention in Transformers.mp4 (296.62 MB)
95 Day 4 Positional Encoding and Feed Forward Networks.mp4 (254.62 MB)
96 Day 5 Hands On with Pre Trained Transformers - BERT and GPT.mp4 (253.93 MB)
97 Day 6 Advanced Transformers - BERT Variants and GPT 3.mp4 (260.49 MB)
98 Day 7 Transformer Project - Text Summarization or Translation.mp4 (236.64 MB)
99 Introduction to Week 13 Transfer Learning and Fine Tuning.mp4 (4.6 MB)
100 Day 1 Introduction to Transfer Learning.mp4 (180.76 MB)
101 Day 2 Transfer Learning in Computer Vision.mp4 (362.2 MB)
102 Day 3 Fine Tuning Techniques in Computer Vision.mp4 (295.76 MB)
103 Day 4 Transfer Learning in NLP.mp4 (220.55 MB)
104 Day 5 Fine Tuning Techniques in NLP.mp4 (343.49 MB)
105 Day 6 Domain Adaptation and Transfer Learning Challenges.mp4 (198.96 MB)
106 Day 7 Transfer Learning Project - Fine Tuning for a Custom Task.mp4 (237.01 MB)]
Screenshot
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