The days are bygone when consumers don’t know what their rights are, today’s consumers are well aware of their rights and duties.
That is why they are constantly demanding high-end goods and services. So companies are focusing more on their products and their quality and delivery.
For producing high-quality goods, they are collecting data from various sources to know about the preferences of people. But as there are billions of people, similarly, the data is massive.
Companies use data science to deal with such a huge chunk of data. But that is not all, to make their work more efficient, they are also using Python, the best programming language.
If you want to know about Data Science With The Python Training course, then you are on the right page where you will get complete information on the course.
Why This Course
This is a course where you will get comprehensive hands-on python training and master it. Through this course, you will get started with python programming and learn how to use it in data science.
You will learn in this course the key concepts in data science like statistics, exploratory data science, regression classification modeling techniques, and hypothesis testing.
Also, you will learn machine learning algorithms which are one of the essential components of data science.
In this course, you will learn,
- What are basic data types, data structures, strings, loops, regular expressions, and control statements
- What are the lambda function, objects in Python, and object-oriented way of writing classes
- How to import datasets into Python, data analysis through Pandas library, and how to write outputs
- How to use data values, conditional probability, data distribution, and hypothesis testing
- How to analyze variance, model building, linear regression, dimensionality reduction techniques
- How to evaluate model parameters, classification problems, and model performance
- How to work with time series data, benefits, components, and tools of it
So in the course, each and every topic related to Python and data science are covered, and you are trained to overcome obstacles in your future work environment.
This course is based on learn by doing approach in which you will get theory classes and practical classes, and you have to do experiments on your own.
You will study the course components better through experiments, real-world assignments, and case studies.
With assignments, you also need to submit your projects which you can later add to your portfolio. You will get appropriate feedback on your assignments and projects for further improvements.
To clear your doubts, you can ask questions and participate in group discussions and panel discussions. Your mentors are industry leaders who have earned decades of experience.
Who Can Choose This Course
This course is perfect for those who want to make a career in data science and python programming.
Some of the major career options after this course are as follows,
- Data scientist
- Python programmer
- Python with data science for big organizations
- Data engineers
- Software engineers
- Engineers
- Researchers
- Economists
- Data analysts
What You Learn In This Course
The course curriculum covers all the related themes of data science and python programming. The units of the syllabus are,
Unit 1 Introduction To Data Science
In this module, you will learn the fundamentals of data science, the analytics landscape, and the tools and technologies used in data science.
Unit 2 Mastering Python
The second unit of the course is based on python training, in which you will learn basic concepts of Python.
You will learn how to install python distribution, data structures in Python, functions and classes in Python, and how to work with data.
Also, you will learn what are control and loop statements in Python, how to analyze data with Pandas, and how to visualize data, followed by a case study.
Unit 3 Probability And Statistics
The third unit of the course includes various theorems of data science through which you will learn the distribution of data in terms of standard deviation, variance, and interquartile range.
You will learn simple graphics analysis and probability with daily life instances. In the course, you will learn marginal probability and how it is important in data science.
Unit 4 Advanced Statistics And Predictive Modeling – I
In this unit, you will learn advanced-level statistics and data science concepts with an analysis of variance and its practical usage.
You will learn in this what is ANOVA, principle component analysis, linear regression, and factor analysis, followed by case studies.
Unit 5 Advanced Statistics And Predictive Modeling – II
This unit is a continued part of the previous unit in which you will learn binomial logistic regression for binomial classification problems.
In this unit, you will learn about the decision tree, K – Nearest neighbor algorithm, and various other themes.
Unit 6 Time Series Forecasting
In this module, you will learn about time series data and what are its components, including trend data, level data, and seasonal data.
Also, you will learn various other models and do case studies to better understand the module.
Unit 7 Capstone Project
This is the last unit of the course in which you will get a real-life project, and under the guidance of your mentor, you have to complete the project.
Through this module, you will clearly see how you will work with enterprises to visualize their data and use Python.
All the units of the course curriculum are balanced so that it doesn’t feel burdensome.
What You Need Before Starting The Course
There are no prerequisites to register for this course however, elementary-level knowledge of data science, statistics, programming languages, and Python is required.
Participants having these skills can get the course content easily and efficiently.
What You Will Accomplish After The Course
After completing this course, you will acquire skills and knowledge of data science and python programming. Both of them are in high demand, and this course will fetch you numerous job opportunities.
With that, it also enhances your portfolio and makes you a valuable asset to organizations. Thus after completing this course, you will be a part of the data scientist and programmer community where you will grow and develop.
