This highly-rated course boasts a 0.0-star-star rating from 0 reviews and has successfully guided 734 students in mastering Other IT & Software skills. Featuring 25 hour(s) 30 minute(s) of expert-led content delivered in English, this course offers thorough training to enhance your Social Science expertise. The course details were last updated on December 24, 2024. This coupon code is brought to you by Anonymous.
- Expires on: 2025/08/02
- Last Update: July 29, 2025
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Price:
49.99 $0 $
About This Course
Master the End-to-End Machine Learning Process with Python, Mathematics, and Projects — No Prior Experience Needed
This course is not just another introductory tutorial. It is a complete and intensive roadmap, carefully crafted for beginners who want to become confident and capable Machine Learning practitioners. Whether you're a student, a job-seeker, or a working professional looking to transition into AI/ML, this course equips you with the core skills, hands-on experience, and deep understanding needed to thrive in today’s data-driven world.
Why This Course Is Different
This masterclass solves both problems by following a clear, layered, and project-oriented curriculum that blends coding, theory, and practical intuition — so you not only know what to do, but why you're doing it.
You’ll go step-by-step from foundational Python to building real ML models and deploying them in real-world workflows — even touching advanced topics like ensemble models, hyperparameter tuning, regularization, and generative AI.
What You’ll Learn — Inside the Masterclass
#______Foundations of Machine Learning and Artificial Intelligence
What is ML, how it differs from AI and Deep Learning.
Key ML model types: Regression, Classification, Clustering.
Understanding AI applications, Gen AI, and the future of intelligent systems.
Knowledge checks to reinforce conceptual understanding.
#______Python Programming from Scratch – for Absolute Beginners
Starting with variables, data types, conditionals, loops, and functions.
Data structures: Lists, Sets, Tuples, Dictionaries with hands-on labs.
Object-oriented programming, API requests, and web scraping with BeautifulSoup.
Reading and writing real-world datasets using pandas.
#______Data Cleaning and Preprocessing – Real-World Essentials
Handling missing values, data types, inconsistencies, and duplicates.
Sorting, slicing, filtering, merging, and concatenating datasets.
Performing these operations with structured labs and real datasets.
#______Feature Engineering – Turning Raw Data into Intelligence
Generating new features from date/time and domain knowledge.
Encoding categorical variables, binning, mapping, and generating dummies.
Prepping datasets to enhance model performance.
#______Exploratory Data Analysis (EDA) and Visualization
Creating distribution plots using KDE.
Checking for normality with Shapiro-Wilk tests.
Performing data transformations (Log, Sqrt, Box-Cox).
Selecting meaningful features and reducing dimensions via PCA.
#______Mathematics for Machine Learning – Build True Intuition
Linear Algebra: Vectors, Matrices, Dot Product, and Transpose.
Understanding tensors and their applications in deep learning.
Grasping the math behind model architecture and training logic.
#______Machine Learning Algorithms – Explained and Built from Scratch
Linear Regression, Logistic Regression, KMeans Clustering.
Decision Trees, Random Forests (Regressor & Classifier).
Building models line-by-line in Python with evaluations and predictions.
Working with real datasets in guided hands-on labs.
#______Advanced Boosting Algorithms – The Industry’s Favorites
AdaBoost, Gradient Boosting (GBM), CatBoost, LightGBM, and XGBoost.
Step-by-step breakdown of how these models work and how to train them.
Understanding when and why to use each one.
#______Model Evaluation, Optimization, and Improvement
K-fold cross-validation, L1 & L2 regularization.
Oversampling & undersampling methods (SMOTE, Tomek Links).
Hyperparameter tuning using GridSearch, RandomSearch & Bayesian methods.
Making your models more robust, fair, and generalizable.
#______Deep Learning Fundamentals with TensorFlow 2.0
Understanding how neural networks learn.
Layers, activation functions, weight initialization (Glorot), and SGD.
Preprocessing data, training neural nets, evaluating and improving DL models.
#______Introduction to Generative AI and Prompt Engineering
AI workflow, types of AI, and Gen AI applications in NLP, vision, and speech.
Prompt engineering: what it is, how it works, and real-world best practices.
Projects like building a chatbot with LLaMA and generating images using Stable Diffusion.
#______Hands-On Real Projects – From Scratch to Deployment
Real-life ML tasks including classification and regression case studies.
Deep learning projects: text-to-image generation and chatbot development.
Walkthroughs of full ML pipelines: cleaning, modeling, evaluating, and presenting results.
Building portfolios worthy of recruiters and hiring managers.
What You’ll Walk Away With
By the end of this course, you’ll have the ability to:
Write clean Python code for machine learning projects.
Understand and explain how various ML algorithms work.
Perform data cleaning, EDA, feature engineering, and model training.
Evaluate and fine-tune models using advanced techniques.
Work on real ML projects that simulate professional work environments.
Understand deep learning fundamentals and generative AI workflows.
Build a portfolio that can help you land entry-level to intermediate ML jobs or freelance gigs.
One Honest Note
This course emphasizes real understanding, not animated fluff. Lessons are code-first, explanation-rich, and designed for learners who want depth, not shortcuts. If you’re ready to invest the effort, the rewards are real.
Final Thought: Your Transformation Starts Here
Machine Learning is not just a hot trend — it’s the future of decision-making, automation, and innovation. But mastering it takes commitment.
This 2025 Machine Learning Masterclass will guide you through that journey step-by-step — helping you not only learn ML, but think like an ML practitioner, and work like one too.
Join now and start your transformation into a Machine Learning expert.
