Python certification training course will help you master the concepts and gain in-depth experience on writing python code and packages like SciPy, Matplotlib, Pandas, Scikit-Learn, NumPy, Web scraping libraries, Lambda Function also you will learn how to write Python code for Big Data systems like Hadoop & spark. As part of the Python certification training course you will be working on real-world projects and case studies and get hands-on experience through online Python lab.
Python training certification course will help you to understand the high-level, general-purpose dynamic programming language. In this Python training course you will be exposed to both the basic and advanced concepts of Python like machine learning, Deep Learning, Hadoop streaming, MapReduce in Python, and work with packages like Scikit and Scipy.
You don’t need any specific knowledge to learn Python. A basic knowledge of programming can help.
Python is a highly popular object-oriented language that is fast to learn and easy to deploy. It can run on various systems like Windows, Linux and Mac thus make it highly coveted for the data analytics domain. Upon completion of Python certification training you can work in the Big Data Hadoop environment for very high salaries.
Nerd Geek Lab follows rigorous certification process, to become a certified Python programmer, you must fulfil the following criteria
What is data science, what does a data scientist do, the various examples of data science in the industries, how Python is deployed for data science applications.
What is data analysis, the various steps in data analysis process like data wrangling, data exploration and selecting the model, understanding data visualization, what is exploratory data analysis, building of hypothesis, plotting and other techniques.
Introduction to Python Language, features, the advantages of Python over other programming languages, Python installation, Windows, Mac & Linux distribution for Anaconda Python, deploying Python IDE, basic Python commands, data types, variables, keywords and more.
Built-in data types in Python, tabs and spaces indentation, code comment Pound # character, variables and names, Python built-in data types, Numeric, int, float, complex, list tuple, set dict, containers, text sequence, exceptions, instances, classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug, basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise, loop and control statements, while, for, if, break, else, continue.
How to write OOP concepts program in Python, connecting to a database, classes and objects in Python, OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation, Python functions, return types, and parameters, Lambda expressions, connecting to database and pulling the data.
Introduction to arrays and matrices, indexing of array, datatypes, broadcasting of array math, standard deviation, conditional probability, coorelation and covariance.
Android broadcast receiver, registering the broadcast receiver, deploying Broadcast() method for broadcasting message, broadcast message listening, using manifest file for registering a receiver, understanding Android notification, creation of notification and working with context menu.
Introduction to SciPy and its functions, building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, SciPy with Bayes Theorem.
How to plot graph and chart with Python, various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotLib, subplots.
Learning about content providers, the concepts, storing data in Android, creation of content provider.
Introduction to Python dataframes, importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe, various data operations like selecting, filtering, sorting, viewing, joining, combining, how to handle missing values, time series analysis, linear regression.
What is natural language processing, working with NLP on text data, setting up the environment using Jupyter Notebook, analyzing sentence, the Scikit-Learn machine learning algorithms, bags of words model, extracting feature from text, searching a grid, model training, multiple parameters, building of a pipeline.
Introduction to web scraping in Python, the various web scraping libraries, beautifulsoup, Scrapy Python packages, installing of beautifulsoup, installing Python parser lxml, creating soup object with input HTML, searching of tree, full or partial parsing, output print, searching the tree.
Introduction to Python for Hadoop, the basics of the Hadoop ecosystem, Hadoop common, the architecture of MapReduce and HDFS, deploying Python coding for MapReduce jobs on Hadoop framework.
Introduction to Apache Spark, importance of RDD, the Spark libraries, deploying Spark code with Python, the machine learning library of Spark MLlib, deploying Spark MLlib for classification, clustering and regression.
This Python online course is designed for clearing the Nerd Geek Lab Python Certification Exam. The entire python training course content is designed by industry professionals to get the best jobs in the top MNCs. As part of this online Python course training you will be working on real time projects and assignments that have immense implications in the real world industry scenario thus helping you fast track your career effortlessly.
At the end of this online Python course there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and helps you score better marks in certification exam.