Complete Data Science,Machine Learning,DL,NLP Bootcamp
Master the theory, practice,and math behind Data Science,Machine Learning,Deep Learning,NLP with end to end projects
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- Downloadable Course
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250
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- Last updated: 08/2026
- English
What you'll learn
✓
Master foundational and advanced Machine Learning and NLP concepts.
✓
Understand and implement mathematical principles behind ML algorithms.
✓
Understand The Core intuition of Deep Learning such as optimizers,loss functions,neural networks and cnn
✓
Apply theoretical and practical knowledge to real-world projects using Machine learning,NLP And MLOPS
✓
Develop and optimize ML models using industry-standard tools and techniques.
This Course Includes
- 101.5 hours on-demand video
- 20 coding exercises
- Access on mobile and TV
Course Content
64 sections • 486 lectures • 101h 27m total length
Getting Started
27min
Python Programming Language
1hr 24min
Python Control Flow
49min
Inbuilt Data Structures In Python
2hr 9min
Functions In Python
1hr 22min
Function Practice Question
0
Inbuilt Data Structure - Practice Question
0
Importing Creating Modules And Packages
36min
File Handling In Python
26min
Exception Handling In Python
26min
OOPS Concepts With Classes And Objects
1hr 56min
Advance Python
39min
Data Analysis With Python
2hr 27min
Working With Sqlite3
17min
Logging In Python
27min
Python Multi Threading and Multi Processing
66min
Memory Management With Python
21min
Getting Started With Flask Framework
1hr 46min
Getting Started With Streamlit Web Framework
26min
Getting Started With Statistics
2hr 24min
Introduction To Probability
22min
Probability Distribution Function For Data
3hr
Inferential Statistics
2hr 31min
Feature Engineering
1hr 24min
Exploratory Data Analysis and Feature Engineering
1hr 39min
Introduction To Machine Learning
1hr 1min
Understanding Complete Linear Regression Indepth Intuition And Practicals
4hr 16min
Ridge,Lasso And ElasticNet ML Algorithms
2hr 10min
Steps By Step Project Implementation With LifeCycle OF ML Project
2hr 44min
Logistic Regression
2hr 7min
Support Vector Machines
1hr 44min
Naive Bayes Theorem
56min
K Nearest Neighbour ML Algorithm
37min
Decision Tree Classifier And Regressor
1hr 47min
Random Forest Machine Learning
1hr 26min
Adaboost Machine Learning Algorithm
1hr 10min
Gradient Boosting
34min
Xgboost Machine Learning Algorithms
1hr 4min
Unsupervised Machine Learning
8min
PCA
1hr 29min
K Means Clustering Unsupervised ML
49min
Hierarchical Clustering
33min
DBSCAN Clustering
26min
Silhouette Clustering
9min
Anomaly Detection Machine Learning Algorithms
38min
Dockers For Beginners
1hr 39min
GIT For Beginners
61min
End To End Machine Learning Project With AWS,Azure Deployment
6hr 16min
End To End MLOPS Projects With ETL Pipelines- Building Network Security System
7hr 41min
MLFlow Dagshub and BentoML-Complete ML Project Lifecycle
1hr 34min
NLP for Machine Learning
6hr 26min
Deep Learning
6hr 44min
End to End Deep Learning Project Using ANN
2hr 17min
NLP With Deep Learning
18min
Simple RNN Indepth Intuition
1hr 43min
End To End Deep Learning Project With Simple RNN
1hr 19min
LSTM And GRU RNN Indepth Intuition
2hr 6min
LSTM And GRU End To End Deep Learning Project- Predicting Next Word
46min
Bidirectional RNN Architecture And Indepth Intuition
23min
Encoder Decoder | Sequence To Sequence Architecture
41min
Attention Mechanism- Seq2Seq Networks
29min
Transformers
6hr 2min
Claude Code- Vibe Coding For Developers
2hr 7min
Role Play
0
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8 Live Doubt-Clearing Sessions
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