The Data Science with Python course is a comprehensive program designed for learners to gain skills in the field of data science and analytics using Python. It covers a wide range of topics from the basics of data science, machine learning, and statistical analysis to advanced topics such as natural language processing and deep learning. The course is structured in a modular fashion, starting with an introduction to data science, and progressively moving through Python programming essentials, data manipulation with Pandas, data visualization with Matplotlib and Seaborn, and machine learning with Scikit-Learn.
Learners will earn a data science with python certification upon completion, which validates their expertise in the field and enhances their job prospects. This course is ideal for those aiming to build a career in data science and for professionals seeking to update their skills with the latest tools and techniques. The curriculum is designed to provide hands-on experience, ensuring that participants are job-ready with a practical understanding of how to solve real-world data problems using Python.
By the end of the course, learners will be well-equipped to handle complex data analysis tasks and build predictive models, making them valuable assets in the data-driven industry.
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4-Hour Sessions
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Classroom Training price is on request
♱ Excluding VAT/GST
Classroom Training price is on request
USD 199+
USD 19+
USD 59+
♱ Excluding VAT/GST
Flexi FAQ'sTo successfully undertake the Data Science with Python course at Koenig Solutions, the following minimum prerequisites are recommended:
These prerequisites are designed to ensure that learners can comfortably grasp the course content and participate actively in the learning process. No advanced knowledge is required, and the course aims to build upon these foundational skills to help learners become proficient in data science using Python.
The "Data Science with Python" course by Koenig Solutions is designed for professionals seeking to harness data for insightful decision-making and predictive analytics.
Gain in-depth knowledge of data science processes, Python programming, and machine learning techniques to analyze data, derive insights, and develop data-driven solutions across various sectors.