The fundamentals of the data science with python course including core python programming techniques like lambdas, reading and manipulating CSV files, and the Numpy library, will be covered in this course. The popular Python pandas data science library will be used to teach students how to manipulate and clean data, explain the abstraction of Series and DataFrame as the key data structures for data analysis, and provide tutorials on how to efficiently use tools like groupby, merge, and pivot tables. Students will be able to take tabular data, clean it up, manipulate it, and perform fundamental inferential statistical analyses by the end of the course.
What will you learn in Data science with Python Course?
- End-to-end knowledge of Data Science
- Python programming -Variables, Data types, Loops, Functions, Tuples, Dictionary, List, Functions & Modules, etc.
- Data science Applications
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
- Decision-making and Regular Expressions
- Data engineering in Pandas
- Data visualization in Excel and Python
- Statistical Methods in Data Science with Python
- Introduction to Data Science Libraries
- Supervised and unsupervised Models
- Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Clustering Analysis
- Reinforcement Learning
- Ensemble Learning
- Model validation and testing
- Regularization(Lasso and Ridge)
- Performance Analysis for Classification problem
- ROC Curve
- Model Specification
- Confusion Matrix
- Data Mining with Python
- Deep Learning and AI
- Tensorflow and Keras overview
- CNN, RNN
- Overview of NLP
- Overview of Tableau
This course does NOT need any pre-requisite. You Just need to have laptop and an Internet connection.
A warm welcome to the Data Science with Python course.
If you aspire to become a data scientist and want to expand your horizons, then this is the perfect course for you. The primary goal of this course is to provide you a comprehensive learning framework to use Python for data science.
This curated Data Science with Python course will take your journey from the fundamentals of Python to exploring simple and complex datasets and finally to predictive analysis & models development. In this Data Science using Python course, you will learn how to prepare data for analysis, perform complex statistical analysis, create meaningful data visualizations, predict future trends from data, develop machine learning & deep learning models, and more.
Data Science with Python involves not only using Python language to clean, analyze and visualize data, but also applying Python programming skills to predict and identify trends useful for decision-making.
Why Python for Data Science?
Since data revolution has made data as the new oil for organizations, today’s decisions are driven by a multidisciplinary approach of using data, mathematical models, statistics, graphs, databases for various business needs such as forecasting weather, customer segmentation, studying protein structures in biology, designing a marketing campaign, opening a new store, and the like. The modern data-powered technology systems are driven by identifying, integrating, storing and analyzing data for useful business decisions.
Scientific logic backed with data provides solid understanding of the business and its analysis. Hence there is a need for a programming language that can cater to all these diverse needs of data science, machine learning, data analysis & visualization, and that can be applied to practical scenarios with efficiency. Python is a programming language that perfectly fits the bill here and shines bright as one such language due to its immense power, rich libraries and built in features that make it easy to tackle the various facets of Data Science.
In the Data Science with Python training you will gain new insights into your data and will learn to apply data science methods and techniques, along with acquiring analytics skills. With understanding of the basic python taught in the initial part of this course, you will move on to understand the data science concepts, and eventually will gain skills to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular Python toolkits such as pandas, NumPy, matplotlib, scikit-learn, and so on.
So lets begin your journey to becoming a top data scientist.
Who is this course for?
1. College Freshers
2. Anyone who is willing to learn data science in simple and easy steps using Python as a programming language