Data Science & Machine Learning Training Program
Our comprehensive 6-week Data Science & Machine Learning training
program is designed to equip you with the skills needed to excel
in the field of data science. Enroll now to master Python, machine
learning algorithms, deep learning, and more through hands-on
projects and expert guidance.
Training Start: Enroll Anytime!
Working Hours: 10:00 AM - 8:00 PM, 6 Days a Week
Location: Doctor's Colony, behind DMart,
Madhapur, Hyderabad
Course Fee: ₹10,000
Our 6-week Data Science & Machine Learning program equips you with
the skills to excel in the industry:
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Week 1: Foundations + Python for ML -
Understand AI vs ML with real-world examples, learn Python
essentials (variables, functions, loops, lists), and work with
NumPy & Pandas for efficient data handling.
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Week 2: Math, Probability & ML Basics - Refresh
key concepts in linear algebra and probability, dive into
Supervised Learning fundamentals, and build your first Linear &
Logistic Regression models.
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Week 3: Core Machine Learning Algorithms -
Learn key ML algorithms (Decision Trees, k-NN), evaluate models
using accuracy, precision, recall, F1-score, and complete
Industry Project 1: Apply ML techniques to real-world datasets
for prediction & classification.
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Week 4: Deep Learning Foundations - Explore
Neural Networks (perceptrons, activation functions), build your
first deep learning model using TensorFlow/Keras, and understand
overfitting, dropout, and regularization. Intro to CNNs and
their role in image recognition.
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Week 5: CNN Project + NLP Basics - Complete
Industry Project 2: Implement a CNN for image-based
classification tasks, introduction to Natural Language
Processing, text preprocessing (tokenization, stopword removal),
build a text classifier using bag-of-words & TF-IDF, visualize
word embeddings, and explore ML model deployment using
Streamlit.
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Week 6: Capstone Project & Demo - Capstone
Industry Project: Apply everything learned to solve a real-world
AI-ML problem, work on model building, tuning, and deployment,
and present your project with code, results, and visualizations.
Download the detailed syllabus to explore the curriculum:
Download Syllabus