Python is becoming an increasingly popular language for data analysis and interactive, exploratory computing and data visualization. It has been the preferred language among Data Scientists.
Python is distinguished by its large and active scientific computing community. Adoption of Python for scientific computing in both industry applications and academic research has increased significantly since the early 2000s. There are people developing “libraries” for virtually anything.
Together with the NumPy, SciPy, ScikitLearn and Matplotlib/Pylab, it provides a nice environment for scientific works and data analytics with python. In recent years, Python’s improved library support (primarily Pandas) has made it a strong alternative for data manipulation tasks. Combined with the power of python for data analytics and a general-purpose programming language, it is an excellent choice as a single language for building data-centric applications.
Python is a highly adaptable programming language that lets you work more rapidly and integrate your systems more effectively. Key features of Python are flexibility, rapid development, scalability, excellent performance and ease of maintenance. You can learn Python and realize immediate improvements in productivity and lower maintenance cost. Python runs on all major operating systems: Windows, Linux/Unix, Mac OS X. Python can be integrated with .COM, .NET, and .CORBA objects. There are implementation of Python for Java libraries and for .NET objects. Python is free to use, even for commercial products, because of its OSI (Open Source Initiative) approved open source license.
Google Cloud Platform offers computing & hosting services for Python applications and various products for storage, machine learning, and big data that can be used from any Python application anywhere. Google released TensorFlow, an open source Python library for fast numerical computation, which can be used to create Deep Learning.
This course begins with an introduction to the Python programming training with basics of the python programming environment, including how to download and install python, fundamental python programming techniques, common Python functionality and features which data scientists use. Basic Python programming classes include syntaxes & semantics of Python for data analysis.
Brush up sessions for various descriptive and inferential statistical measures and techniques will be conducted followed by real-world data cleaning, merging, manipulating, test for significance in data using the popular python library pandas and Data visualization techniques using MatplotLib.
Popular Python libraries like NumPy, SciPy, MatplotLib, Pandas, ScikitLearn for efficient machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction will be explained in depth along with extensive hands on sessions.
Exhaustive assignments on supervised and unsupervised machine learning algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machine, K Means Clustering, K-Nearest Neighbor (K-NN), Principal Components Analysis (PCA), Gaussian Mixture Model (GMM) will be systematically worked out in the class with the purpose of making the learner confident in data science with python, and a great learning experience in one the best Python training institutes in Pune. At the completion of this course, the learner will be able to get up to speed on how to implement top machine learning algorithms from scratch in Python.
The content of our “Python for Data Science & Analytics” course is developed and being taught by professional Data Scientists from leading multinational companies with broad experience in extracting meaning from large data sets using a wide variety of techniques in machine learning, data mining, and data science using Python programming language.
This course presents most applied machine learning techniques with clear practical examples of data science in python.
This course is intended for learners, who are looking for classroom Python training in Pune, to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through Python scientific libraries such as Numpy, SciPy, Pandas, MatplotLib, ScikitLearn to gain insight into their data.
Learners are expected to have some familiarity with Machine Learning basics, knowledge of Data Science, basic Statistical concepts along with basic computer programming concepts, who can pick up this language relatively quickly. Those who have no familiarity with Machine Learning concepts, should take up our Data Science Professional course with R and Python.
Learning aspirants searching for python online course or python training online may contact us for details. Aspirants might have been tempted by the benefits of online python course or a python online tutorial, but need to carefully choose the training mode. Classroom training has been more effective than the python course online. However, aspirants constrained with geographical limitation may also opt for online python training with us.
Earn a MARSIAN certificate of completion at end of the course. Additionally, you will also get necessary support for any external certification preparation.