Next-Gen Data Analytics & AI Mastery: From Insights to Intelligence
Master Python programming, data analysis, and machine learning with hands-on projects and real-world datasets. Gain industry-ready skills in modern AI, including neural networks, deep learning, and LLMs.
1 instructor teaches this course
10
menu_book
Classes & activities
Starts at
₹11,799Inclusive of GST
What you'll be able to do after completing these classes
done
Build strong foundations in Python programming for data analysis
done
Perform data cleaning, preprocessing, and transformation using NumPy and Pandas
done
Apply machine learning algorithms and understand modern AI concepts including neural networks, deep learning, and LLMs
Classes and Activities
person_outline
Session 1: Python Basics – Variables, Data Types, Control Flow, Functions
2 hrs
expand_more
Kick off your analytics journey by learning Python basics. This session covers variables, core data types, conditional statements, loops, and function creation. Through hands-on coding exercises, you'll build a strong foundation for all future data analytics and AI work.
Deepen your Python expertise by working with file input/output, exploring the Python Standard Library, and getting an overview of essential data science libraries. Engage in practical exercises to reinforce concepts and prepare for data manipulation tasks.
Discover the power of NumPy for scientific computing. You'll practice creating and manipulating arrays, performing vectorized operations, and leveraging NumPy's mathematical functions to accelerate data analysis workflows.
person_outline
Session 4: Pandas – DataFrames, Data Cleaning, Transformation
2 hrs
expand_more
Get hands-on with Pandas to load, clean, and transform real-world datasets. You'll learn to handle missing data, filter and aggregate information, and prepare data for analysis and modeling.
person_outline
Session 5: EDA and Visualization with Matplotlib & Seaborn
2 hrs
expand_more
Develop skills in exploratory data analysis (EDA) by creating insightful visualizations. You'll use Matplotlib and Seaborn to plot distributions, relationships, and trends, enabling you to draw meaningful conclusions from data.
person_outline
Session 6: Statistics for ML + Feature Engineering
2 hrs
expand_more
Learn core statistics concepts relevant to machine learning, including probability, distributions, and hypothesis testing. Practice feature engineering techniques to enhance model performance and prepare data for ML algorithms.
Dive into supervised learning with regression algorithms. You'll build, evaluate, and interpret linear, ridge, and lasso regression models using real datasets, learning how to select and tune models for predictive analytics.
Master classification techniques by implementing logistic regression, support vector machines, decision trees, and random forests. You'll compare their strengths and weaknesses and apply them to real-world classification problems.
person_outline
Session 9: Clustering + Intro to Reinforcement Learning
2 hrs
expand_more
Learn unsupervised learning through clustering algorithms like K-Means and hierarchical clustering. Get introduced to reinforcement learning concepts and see how agents learn from environments.
Explore the fundamentals of neural networks and deep learning. Get an overview of advanced architectures such as Transformers and large language models (LLMs), understanding their impact on modern AI applications.
About the course
This instructor-led course is designed to equip learners with a comprehensive foundation in Python programming for data analytics and machine learning. Through a blend of theory and hands-on practice, participants will learn to clean and preprocess data using NumPy and Pandas, perform exploratory data analysis with Matplotlib and Seaborn, and apply statistical thinking to real-world datasets. The course covers essential machine learning algorithms for regression, classification, and clustering, and introduces advanced AI concepts such as neural networks, deep learning, reinforcement learning, and modern architectures like Transformers and LLMs. Delivered by experienced professionals, the curriculum emphasizes practical skills and job readiness, making it ideal for aspiring data analysts and ML practitioners.
Availability
4 enrollment options available
Apr 27 (Mon)
7:00 AM
computer
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Yuno Learning
Apr 25 (Sat)
7:00 AM
computer
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Yuno Learning
Apr 28 (Tue)
7:00 AM
computer
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Yuno Learning
Apr 25 (Sat)
4:00 PM
computer
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Yuno Learning
About the academy
Boost your skills with expert-led Booster Leap programs by AiToNi Edutech. Explore Data Science, AI/ML, and languages while building a strong academic foundation. Designed for all levels, these courses blend technology and learning to keep you future-ready.