Master Data Science, Machine Learning & AI With Expert Guidance

By DeepLearnAcademy • AIML • 60 hours • 28 students enrolled

About This Course

Unlock Your Future in Data Science, Machine Learning & AI Are you ready to become an industry-ready Data Scientist and AI Professional? This comprehensive course, "Master Data Science, Machine Learning & AI With Expert Guidance," is designed to take you from fundamentals to advanced concepts with hands-on projects, real-world applications, and expert mentoring. Whether you’re a beginner looking to enter the world of data or a professional aiming to upskill, this course will equip you with the knowledge, confidence, and practical expertise to thrive in one of the fastest-growing and most in-demand fields.

Course Content

AI & ML Orientation: Introduction and Course Structure - Part 1

Recorded Video • 36 minutes

AI & ML Orientation: Introduction and Course Structure - Part 2

Recorded Video • 20 minutes

Module 1 - Introduction to Python - Python Fundamentals & Jupyter Notebooks: A Practical Introduction - Part - 1

Recorded Video • 30 minutes

Module 1 - Introduction to Python - Python Fundamentals & Jupyter Notebooks: A Practical Introduction - Part - 2

Recorded Video • 30 minutes

Module 1 - Python Basics for Machine Learning

Recorded Video • 60 minutes

Module 1 - Exploring Python Functions, NumPy, and Pandas through Hands-on Coding

Recorded Video • 60 minutes

Module 1 - Data Exploration and Visualization using Pandas and Matplotlib - Part 1

Recorded Video • 60 minutes

Module 1 - Data Exploration and Visualization using Pandas and Matplotlib - Part 2

Recorded Video • 60 minutes

Module 1 - Assignment Discussion and Conclusion of Python for Machine Learning

Recorded Video • 45 minutes

10.

Module 2 - Session 1 - Statistics

Recorded Video • 60 minutes

11.

Module 2 - Session 2 - Statistics

Recorded Video • 60 minutes

12.

Module 2 - Session 3 - Statistics

Recorded Video • 60 minutes

13.

Module 2 - Statistics: Probability Distribution Explained

Recorded Video • 60 minutes

14.

Module 2 - Bayes’ Theorem: Understanding and Practical Applications

Recorded Video • 60 minutes

15.

Module 3 - Introduction to Exploratory Data Analysis (EDA) and Basics

Recorded Video • 60 minutes

16.

Module 3 - Univariate, Bivariate, and Multivariate Analysis

Recorded Video • 60 minutes

17.

Module 3 - Understanding and Detecting Outliers in Data

Recorded Video • 60 minutes

18.

Module 3 - Handling Outliers and Data Preprocessing

Recorded Video • 60 minutes

19.

Module 3 - Transforming Outliers and Data Transformation Methods

Recorded Video • 60 minutes

20.

Module 3 - Feature Engineering for Machine Learning

Recorded Video • 60 minutes

21.

Module 3 -Practicals on Data Preprocessing and Feature Engineering

Recorded Video • 60 minutes

22.

Module 3 - Exploratory Data Analysis (EDA) – Practicals

Recorded Video • 60 minutes

23.

Module 3 - Exploratory Data Analysis (EDA) and Synthetic Data Generation

Recorded Video • 60 minutes

24.

Module 3 - General Discussion + Revision

Recorded Video • 60 minutes

25.

Module 3 - General Guidelines for Module 3 and AI Application Tools – Practical Examples

Recorded Video • 60 minutes

26.

Module 4 - Introduction to Machine Learning and Its Types

Recorded Video • 60 minutes

27.

Module 4 - Conceptual and Practical Understanding of the Linear Regression Model

Recorded Video • 60 minutes

28.

Module 4 - Gradient Descent Algorithm: Conceptual and Practical Explanation

Recorded Video • 60 minutes

29.

Module 4 - Machine Learning Model Deployment – Practical Demo

Recorded Video • 60 minutes

30.

Module 4 - Model Evaluation Metrics for Machine Learning

Recorded Video • 60 minutes

31.

Module 4 - Linear & Logistic Regression: Metrics Evaluation, R² Score, and Entropy

Recorded Video • 60 minutes

32.

Module 4 - Logistic Regression and Precision–Recall Evaluation

Recorded Video • 60 minutes

33.

Module 4 - Logistic Regression – Practical Explanation and Implementation

Recorded Video • 60 minutes

34.

Module 4 - Precision, Recall, F1 Score & KNN – Model Evaluation and Practical Understanding

Recorded Video • 60 minutes

35.

Module 4 - Supervised Machine Learning – Support Vector Machines (SVM) Explained

Recorded Video • 60 minutes

36.

Module 4 - Introduction to Unsupervised Machine Learning and Its Types

Recorded Video • 60 minutes

37.

Module 4 - K-Means Clustering, Elbow Method, and Finding the Optimal K Value

Recorded Video • 60 minutes

38.

Module 4 - K-Means Clustering Real-Life Example and Introduction to DBSCAN

Recorded Video • 60 minutes

39.

Module 4 - Machine Learning Module – Summary and Conclusion

Recorded Video • 60 minutes

40.

Module 5 - Introduction to Ensemble Techniques in Machine Learning

Recorded Video • 60 minutes

41.

Module 5 - Introduction to Decision Trees: Gini Impurity, Entropy, and Information Gain

Recorded Video • 60 minutes

42.

Module 5 - Deep Dive into Decision Trees and Gini Impurity

Recorded Video • 60 minutes

43.

Module 5 - Understanding Random Forest and Its Practical Implementation

Recorded Video • 60 minutes

44.

Module 5 - AdaBoost – Boosting Model Performance with Ensemble Learning

Recorded Video • 60 minutes

45.

Module 5 - Revision – Mastering Ensemble Techniques

Recorded Video • 60 minutes

46.

Module 5 - Ensemble Learning – Understanding Stacking Techniques

Recorded Video • 60 minutes

47.

Module 6 - Model Selection & Tuning – Parameters vs Hyperparameters Explained

Recorded Video • 60 minutes

48.

Module 6 - Model Optimization using GridSearchCV & RandomSearchCV

Recorded Video • 60 minutes

49.

Module 6 - Feature Scaling, Transformation & Understanding Data Leakage

Recorded Video • 60 minutes

50.

Module 6 - Building and Understanding Machine Learning Pipelines – Concept & Practical

Recorded Video • 60 minutes

51.

Module 6 - Pipeline Creation & Management | Model Deployment(Basics)

Recorded Video • 60 minutes

52.

Module 7 - Featurization Techniques - Lesson 1

Recorded Video • 40 minutes

53.

Module 7 - Featurization Techniques - Lesson 2

Recorded Video • 40 minutes

54.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session 3 - Part - 1

Recorded Video • 15 minutes

55.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session 3 - Part - 2

Recorded Video • 15 minutes

56.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session3 - Part - 3

Recorded Video • 15 minutes

57.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session 4 - Part - 1(Revision)

Recorded Video • 30 minutes

58.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session 4 - Part - 2(Coding+Gensim+Word2Vec)

Recorded Video • 30 minutes

59.

Module 7 - Learning Text Analysis: Unraveling TF-IDF and Word2Vec - Session 4 - Part - 3(general + Q&A)

Recorded Video • 15 minutes

60.

Module 7 - Featurization Techniques - Vectorization, Vector Embedding, and Vector Space explained - Part 1

Recorded Video • 30 minutes

61.

Module 7 - Featurization Techniques - Vectorization, Vector Embedding, and Vector Space explained - Part 2

Recorded Video • 30 minutes

62.

Module 7 - Featurization Techniques - Dimensionality Reduction, Introduction to PCA

Recorded Video • 20 minutes

63.

Module 7 - Featurization Techniques - Principal Component Analysis unfolded - going beyond the basics - Part 1

Recorded Video • 30 minutes

64.

Module 7 - Featurization Techniques - Principal Component Analysis unfolded - going beyond the basics - Part 2

Recorded Video • 30 minutes

65.

Module 8 - Recommendation Systems - Content-Based + Cosine Similarities Explained - Part - 1

Recorded Video • 30 minutes

66.

Module 8 - Recommendation Systems - Content-Based + Cosine Similarities Explained - Part - 2

Recorded Video • 30 minutes

67.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 1

Recorded Video • 20 minutes

68.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 2

Recorded Video • 15 minutes

69.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 3

Recorded Video • 15 minutes

70.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 4

Recorded Video • 15 minutes

71.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 5

Recorded Video • 15 minutes

72.

Module 8 - Recommendation System - Building Recommendation Systems with Cosine Similarity - Practical + Revision - Part - 6

Recorded Video • 15 minutes

73.

Module 8 - Recommendation System - Pearson Correlation for Smart Recommendation - Part - 1

Recorded Video • 20 minutes

74.

Module 8 - Recommendation System - Pearson Correlation for Smart Recommendation - Part - 2

Recorded Video • 20 minutes

75.

Module 8 - Recommendation System - Pearson Correlation for Smart Recommendation - Part - 3

Recorded Video • 20 minutes

76.

Module 8 - Recommendation System - Pearson Correlation for Smart Recommendation - Part - 4

Recorded Video • 15 minutes

77.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 1

Recorded Video • 20 minutes

78.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 2

Recorded Video • 20 minutes

79.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 3

Recorded Video • 20 minutes

80.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 4

Recorded Video • 20 minutes

81.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 5

Recorded Video • 20 minutes

82.

Module 8 - Recommendation System - Recap & Practical Coding in Recommender Systems - Part - 6

Recorded Video • 20 minutes

83.

Module 8 - Recommendation System - Using Surprise’s SVD on Kaggle: Matrix Factorization in Recommender Systems

Recorded Video • 60 minutes

84.

Module 9 - Computer Vision - Pixels to Pictures: The Magic of Image Processing

Recorded Video • 60 minutes

85.

Module 9 - Computer Vision - Deep Dive into CNN: Powering AI Vision - Part - 1

Recorded Video • 60 minutes

86.

Module 9 - Computer Vision - Deep Dive into CNN: Powering AI Vision - Part - 2

Recorded Video • 25 minutes

87.

Module 9 - Computer Vision - Deep Dive into CNN: Powering AI Vision - Part - 3

Recorded Video • 25 minutes

88.

Module 9 - Computer Vision - Deep Dive into CNN: Powering AI Vision - Part - 4

Recorded Video • 25 minutes

89.

Module 9 - Computer Vision - Deep Dive into CNN: Powering AI Vision - Part - 5

Recorded Video • 20 minutes

90.

Module 9 - CNN - Activation Functions Demystified: Powering Neural Networks

Recorded Video • 60 minutes

91.

Module 9 - Human, Face, Gender & Age Detection using Computer Vision

Recorded Video • 120 minutes

92.

Module 10 - Neural Networks & Deep Learning - Unlocking the AI Brain: Fundamentals of Neural Networks & Deep Learning 🧠

Recorded Video • 60 minutes

93.

Module 10 - Building Neural Networks with TensorFlow and Keras

Recorded Video • 70 minutes

94.

Module 10 - Backpropagation and Optimization Techniques in Deep Learning

Recorded Video • 120 minutes

95.

Module 10 - Improving Model Performance: Overfitting, Dropout, & Batch Normalization

Recorded Video • 60 minutes

96.

Module 10 - From Zero to Deployment: Deep Learning for Real-World Applications

Recorded Video • 60 minutes

97.

Bridging the Gap: Advanced Machine Learning Recap & Reinforcement Session

Recorded Video • 60 minutes

98.

Revision Session – Strengthen What We’ve Learned So Far

Recorded Video • 60 minutes

99.

Module 11 - Neural Networks to NLP: The Essential Bridge to Understanding Human Language AI

Recorded Video • 60 minutes

100.

Module 11 - [NLP] Text Intelligence: From Representation to Sentiment Analysis

Recorded Video • 60 minutes

101.

Module 11 - Hands-On NLP: Code & Create - Practical

Recorded Video • 60 minutes

102.

Module 11 - Introduction to Hugging Face: Bridging Humans and Transformers

Recorded Video • 90 minutes

103.

Module 11 - Hands-on with Hugging Face – Saving & Loading Models, Tokenizers, and Pipelines

Recorded Video • 60 minutes

104.

Module 11 - Mastering Transformer Fine-Tuning: Build Smarter NLP Models with Hugging Face

Recorded Video • 60 minutes

105.

Module 12 - Unlocking the Power of Large Language Models (LLMs): From GPT to Prompt Engineering

Recorded Video • 60 minutes

106.

Module 12 - Mastering Prompt Engineering & Building Local LLM Applications

Recorded Video • 60 minutes

107.

Module 12 - LSTM from Scratch: Building a Mini Text Generator

Recorded Video • 60 minutes

108.

Module 13 - Learning LangChain & RAG: Build Next-Gen AI Applications

Recorded Video • 60 minutes

109.

Module 13 - LangChain + RAG: The Future of Intelligent AI Apps

Recorded Video • 60 minutes

110.

Module 13 - LangChain: Building Intelligent Applications with LLMs

Recorded Video • 60 minutes

111.

Module 13 - Building Intelligent Document Q&A: From RAG Mastery to Advanced AI Agents

Recorded Video • 60 minutes

112.

Module 13 - Agentic AI in Action: LangGraph, MCP, and Browser Automation

Recorded Video • 60 minutes

113.

Module 14 - Capstone Project Discussion & Team Formation Session

Recorded Video • 60 minutes

₹6,999.00

One-time payment • Lifetime access

Industry-recognized certificate

Live 1:1 Mentorship

113+ structured, in-depth lessons

Hands-on practical implementation

Industry-ready projects

Downloadable resources & practical notes

Designed for working professionals · No hidden charges