infyni

Live Data Science & Introduction to Machine Learning

Explore the realms of Data Science and Machine Learning in real-time with our 'Live Data Science & Introduction to Machine Learning' course. Develop a strong foundation in data analysis, statistical modeling, and predictive analytics using Python and key Machine Learning concepts.

Live Course

Live Class: Wednesday, 17 Jan

Duration: 30 Hours

Enrolled: 0

Offered by: infyni

Live Course

About Course

Dive into the world of Data Science and Machine Learning with our comprehensive 'Live Data Science & Introduction to Machine Learning' course. This program serves as your gateway to understanding the fundamentals of data analysis, statistical modeling, and predictive analytics. Covering essential tools like Python, libraries such as Pandas and NumPy, and Machine Learning concepts, this course equips learners with hands-on experience in data manipulation, visualization, and predictive modeling. Led by industry experts, this live training provides the foundational knowledge to kickstart your journey into the realm of data-driven decision-making.

Skills You Will Gain

Data Analysis Fundamentals Python for Data Science Data Visualization Statistical Analysis Introduction to Machine Learning Predictive Modeling Feature Engineering and Selection Model Evaluation and Validation

Course Offerings

Instructor-led interactive classes
Clarify your doubts during class
Access recordings of the class
Attend on mobile or tablet
Live projects to practice
Case studies to learn from
Lifetime mentorship support
Industry specific curriculum
Certificate of completion
Employability opportunity

Topics
Instructor (1)

1 Introduction

2 Optimization and its application in Machine learning

3 Statistical Inference

4 An introduction to linear algebra for Machine Learning

5 Exploratory Data Analysis and the Data Science Process

6 Basics of Machine Learning and Introduction to statistical learning

7 Introduction to simple Linear & Multiple Linear Regression

8 Case Study on Regression using kaggle data set

9 Regularization as a general concept and its use in Linear Regression

10 General intuition behind feature engineering and its relevance in Machine learning

11 Introduction to Classification Algorithms

12 Case study on classification Using real life data set( Kaggle / Analytics Vidya)

13 Feature selection methods and their relevance

14 Clustering

15 Neural Networks and Deep Learning (FFN, CNN, RNNs)

16 Model Agnostics: Unearthing black box models like GBM, XGBoost, Neural Nets, etc

Saurabh lal

About Instructor

I come from a mathematical background and love mentoring students. Teaching is more than a profession for me, So every engagement with my students is special.

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