Numpy
Python
Machine Learning
Statistics Fundamentals
Introduction to Data Science
Begin your journey with an overview of Data Science, exploring its lifecycle and diverse applications. This module introduces you to essential tools and technologies, setting the foundation for your data science journey.
Programming for Data Science
Master the programming languages crucial for data science. Learn Python basics, including data structures and libraries such as NumPy and Pandas. Gain proficiency in R, focusing on data manipulation with dplyr and data visualization with ggplot2.
Data Analysis and Visualization
Dive into exploratory data analysis (EDA) to uncover patterns and insights. This module covers data cleaning and preprocessing, alongside visualization techniques using tools like Matplotlib, Seaborn, and advanced visualization methods.
Statistics and Probability
Build a strong statistical foundation with descriptive and inferential statistics. Understand probability theory and hypothesis testing, essential for making data-driven decisions.
Machine Learning
Discover the world of machine learning, starting with supervised learning techniques such as linear regression, logistic regression, decision trees, support vector machines, and ensemble methods. Explore unsupervised learning through clustering techniques and principal component analysis (PCA). Learn how to evaluate and tune your models for optimal performance.
Advanced Machine Learning
Advance to complex topics like neural networks and deep learning. Understand the principles of neural networks, delve into convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and explore natural language processing (NLP) and time series analysis.
Big Data Technologies
Get introduced to the realm of big data, focusing on the Hadoop ecosystem. Learn about HDFS and MapReduce, essential components for handling large-scale data processing.
1 DS Introduction to Python
2 DS Data Analysis
3 DS Statistics
4.DS Supervised learning 1
5.DS Supervised learning 2
6.DS Supervised learning 3
7.DS Supervised learning 4
8 DS Supervised learning 5
9 DS Supervised learning 6
10 DS Supervised learning 7
11 DS Supervised learning 8
12 DS Supervised learning 9
13 DS Supervised learning 10
14 DS Supervised learning 11
15 DS Supervised learning 12
16 DS Supervised learning 13
17 DS Unsupervised learning1
18 DS Unsupervised learning2
19 DS Unsupervised learning3
20 DS Unsupervised learning4
21 DS Agents
22 DS Neural Networks Intro
23 DS Neural Network Arch
24 DS Multi Layer NNA
25 DS Deep Learning
26 DS Intro to NLP
27 DS Text Pre-Processing part 1
28 DS Text Pre-Processing part 2
29 DS nlp final
30 DS Time Series Analysis & Machine Learning Pipelines
31 DS Big Data Analytics & Anomaly Detection
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9 months ago
i have some doubts about the 1 session otherwise today's session is amazing
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