Manual Testing

Machine Learning and its Benefits

Lesson 1 – Python Basics
Lesson 2 – Python Data Structures
Lesson 3 – Python Programming Fundamentals
Lesson 4 – Working with Data in Python
Lesson 5 – Working with NumPy Arrays

Data Science Course with Python

Key Learning Objectives of Data Science Course in Hyderabad

• Gain an in-depth understanding of Data Science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing.
• Install the required Python environment and other auxiliary tools and libraries.
• Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions.
• Perform high-level mathematical computing using the NumPy package and its vast library of mathematical functions.
• Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave.
• Perform data analysis and manipulation using data structures and tools provided in the Pandas package.
• Gain expertise in Machine Learning using the Scikit-Learn package.
• Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline.
• Use the Scikit-Learn package for natural language processing.
• Use the matplotlib library of Python for data visualization.
• Extract useful data from websites by performing web scraping using Python.

Data Science Course curriculum

Lesson 1 – Data Science Overview.
Lesson 2 – Data Analytics Overview.
Lesson 3 – Statistical Analysis and Business Applications.
Lesson 4 – Python Environment Setup and Essentials.
Lesson 5 – Mathematical Computing with Python (NumPy).
Lesson 6 – Scientific Computing with Python (Scipy).
Lesson 7 –Data Manipulation with Pandas.
Lesson 8 – Machine Learning with Scikit–Learn.
Lesson 9 – Natural Language Processing with Scikit Learn.
Lesson 10 – Data Visualization in Python using Matplotlib.
Lesson 11 – Web Scraping with BeautifulSoup.

• What is Deep Learning?
• What is Data?
• Data Preprocessing and its implementations.
• Exploratory Data Analysis.
• Feature Engineering and Extraction.
• Data Wrangling.
• Data Manipulation.
• Data Visualization.
• Statistics.
• Linear Algebra.
• Calculus
• Data Science Course in Hyderabad- Machine Learning
• Supervised Problems
• Unsupervised Problems
• Semi-Supervised Problem
• Supervised Algorithms

Linear Regression

• Correlation Analysis
• Principles of Regression
• Introduction to Simple Linear Regression
• Python Flask
  • Introduction to Python Flask (deployment)
• Multiple Linear Regression
• Description: Learn about Linear Regression, components of Linear Regression viz regression line, Linear Regression calculator, Linear Regression equation. Get introduced to Linear Regression analysis, Multiple Linear Regression and Linear Regression examples.