Data Science is one of the advancing fields of the industry if we see it in terms of its scope for business and wide job opportunities. Python is as a matter of fact the most popular programming language amongst all and has become the preferred language for Data Scientists. If an individual is skilled in Python language with Data Science, they are in a good position likely to be hired as a skilled Data Scientist.
If you are someone looking for a perfect professional course and certification to master Data Science with Python, KnowledgeHut has a good opportunity for you. They are offering the latest Data Science with Python Course on its immersive learning platform for those interested individuals willing to gain a hands-on experience in Data Science and Python and accelerate their career growth to being an expert Data scientist.
To further know about the course in detail, let us dive into this informative article:
Overview of the Data Science with Python Course
The KnowledgeHut Data Science with Python Course is a comprehensive training program to help the learners gain an understanding of the Python language, its usage, and how one can analyze and visualize data using Scikit, Pandas, and Matplotlib. Training will be provided by the industry experts themselves, who have extensive years of experience in this field, to help you create strong predictive models with advanced statistics. You will learn how to make a sound decision leveraging inferential statistics and hypothesis testing.
The course is an extensive course of 4 weeks which provides a great platform for you to grow your Data Science Skills with Python to have a bright future career. The course covers both the theoretical and practical aspects so that you get the best of the two worlds and eventually learn how to immediately apply the skills learned in the real world. You will be equipped with the requisite skills needed to work with a large number of data sets and build predictive models, and also tell compelling stories to stakeholders.
By the end of the course, you gain an understanding of how the end-to-end data science process works, covering everything that is required to know how to derive value even from complex data. By the end, you’ll be sufficiently able to communicate data insights through data visualizations. For the capstone of your career, you are also trained in putting machine learning models into production so that you can address a real-world data challenge and master concepts of Data Science with Python applications.
The Importance of Data Scientists across Industries
Data Scientists are highly sought after in every field across industries. As per the Emerging Jobs Report of LinkedIn, Data Science has bagged the top position for the last consecutive three years. There are a huge number of companies that need team members who have the ability to transform data sets into strategic forecasts. So, if you want to meet the needs of potential recruiters, you must acquire in-demand Data Science and Python skills. These skills help you a lot in making your career as a Data Scientist.
As brands across the world are realizing the importance of Data Science and Artificial Intelligence, it has taken the Centre stage in the post-COVID world. As per the report by PayScale, the demand for hiring Data Engineers has risen to 50% and for Data Scientists it is 32% in comparison to the previous year’s statistics. PayScale reports that an average annual salary of a Data Scientist in the U.S. is around $96,494 per annum and it’s expected that the demand for data scientists will grow by 16% between the years 2020 and 2028, a rate that is way higher than the average for all occupations. So, it is strongly advised that you capitalize on the demand for the ‘hottest job of the 21st century by learning requisite skills that are in demand across industries.
Things You Will Get to Learn from the Data Science with Python Course
1. Python Distribution: Learn every aspect of Python Distribution such as Anaconda, control statements, basic data types, regular expressions and strings, loops, and data structures.
2. User-defined functions in Python: Master the user-defined functions of Python like Lambda function and the object-oriented way of writing objects and classes.
3. Datasets and manipulation: Learn how to import datasets into Python, write defined outputs, and data analysis using the Pandas library.
4. Probability and Statistics: Explore the functioning of probability and statistics such as data values, conditional probability, data distribution, and hypothesis testing.
5. Advanced Statistics: Master advanced statistics with adequate strategies for the analysis of variance, model building, linear regression, and dimensionality reduction techniques.
6. Predictive Modelling: Master predictive modeling and evaluation of model performance, model parameters, and classification problems.
7. Time Series Forecasting: Discover how to work on Time Series Data, its components, and tools.
There are as such no prerequisites that you need to fulfill in order to take up the Data Science with Python training program. However, participants who come up with having at least some elementary knowledge of programming are likely to make the most out of this course.
The training will be delivered in a unique and interactive way in which you can listen, learn, and even ask questions to get your doubts clarified. It will indeed be a personalized experience when communicating with your expert instructors.
So, without any further ado, enroll in this Data Science with Python Course on KnowledgeHut and accelerate your career growth in the right direction.
|CRITERIA||CHECKLIST||Yes Or No|
|Trademark Compliance||Do the certification names have trademarks?||no|
|General Guidelines||Is KnowledgeHut mentioned in third person?||Yes|
|Are sources cited wherever statistics are included?||Yes|
|Structure||Is there a clear flow of content across the blog?||Yes|
|Is there an introductory paragraph?||Yes|
|Is there a closing paragraph?||Yes|
|Grammar, Style||Are all headings in title case?||Yes|
|Are all the sentences grammatically, correct?||Yes|
|Information Accuracy||Is all the information provided accurate?||Yes|