This course will help you to gain expertise in the usage of Python to learn Data Science.This is a Combo Training Course that will help you implement Python programming in the world of Data Science. This Python for Data Science Master Program has been designed by industry experts taking into consideration the specific needs of businesses today. The Training will provide you with complete expertise in data analysis, data visualization, machine learning, and more..
Introduction to Data Science, importance of Data Science, statistical and analytical methods, deploying Data Science for Business Intelligence, transforming data, machine learning and introduction to Recommender systems.
How Data Science solves real world problems, Data Science Project Life Cycle, principles of Data Science, introduction to various BI and Analytical tools, data collection, introduction to statistical packages, data visualization tools, R Programming, predictive modelling, machine learning, artificial intelligence and statistical analysis.
Boxplot in R programming, understanding distribution and percentile, identifying outliers, Rstudio Tool, various types of distribution like Normal, Uniform and Skewed.
Deploying machine learning for data analysis, solving business problems, using algorithms for searching patterns in data, relationship between variables, multivariate analysis, interpreting correlation, negative correlation.
Data Transformation key phases Data Mapping and Code Generation, Data Processing operation, data patterns, data sampling, sampling distribution, normal and continuous variable, data extrapolation, regression, linear regression model.
Data analysis, hypothesis testing, simple linear regression, Chi-square for assessing compatibility between theoretical and observed data, implementing data testing on data warehouse, validating data, checking for accuracy, data operational monitoring capabilities.
Various techniques of data modelling and generating algorithms, methods of business prediction, prediction approaches, data sampling, disproportionate sampling, data modelling rules, data iteration, and deploying data for mission-critical applications.
Working with large datasets in data warehouses, data clustering, grouping, horizontal & vertical slicing, data sharding in partitioning, clustering algorithms, K-means Clustering for analysing and data mining, exclusive clustering, hierarchy clustering, Mahout Clustering algorithm and Probabilistic Clustering, nearest neighbour search, pattern recognition, and statistical classification.
Introduction to R statistical computing and graphics, concepts, features and advantages of R, Big Data Hadoop familiarity, integrating R and Hadoop, basic architecture, framework, installing RImpala packages.
Introduction to Python, installation of Python, Anaconda Python distribution for Windows, Mac, Linux, input, Jupyter notebook installation, variable assignment, object oriented programming, inheritance, class, method, object variables, control statement, datatypes integer, float, string and output command, for, while loop, accessing and slicing tuples, basic operators, functions, control flow, array manipulation, advanced slicing, beautiful soup, navigation tree, creating own module, module name, dir function, docstring.
Overview of NumPy, properties, purpose and types of array, class and attributes of array objects, basic operations, slicing, indexing, iteration, indexing, accessing array elements, ND-array object, datatype, universal function, shape manipulation, linear algebra,broadcasting, dataframe, panel, array for existing data, numerical range, NumPy indexing and slicing.
SciPy and its characteristics, SciPy sub-packages for integration, optimization, statistics, weave.
Introduction to Pandas, creating Dataframes, datastructures, missing value, series, data operations, data standardization, Pandas file read and write support, SQL operation, Groupby, creating series from dictionary, exception, Pandas series, accessing data from series.
The file system in Python, defining a class, handling of file, various types of exception handling, API in Python database, Python SQLite.
Understanding Hadoop and its various components, Hadoop ecosystem and Hadoop common, HDFS and MapReduce Architecture, Python scripting for MapReduce Jobs on Hadoop framework.
Understanding Python core concepts, familiarizing with the Python Dictionary, various Functions in Python including Lambda function, extensive Python Libraries.
Managing the Sandbox, learning about Sandbox remote login, working with HDFS file system and the Mapper and Reducer functions.
Introduction to natural language processing (NLP), NLP approach for text data, environment setup, sentence analysis, applications, major libraries, built-in modules, approach feature extraction, bag of words, model training, search grid, multiple parameters, pipeline.
Introduction to Python web scraping, web scraping libraries, installation of beautiful soup, common data and page format on the web, importance & kinds of objects, Navigable String, understanding & searching tree, navigating options, the parser, search tree, search by CSS class, list, function and keyword argument.
Project 1 – Understanding Cold Start Problem in Data Science
This project involves understanding of the cold start problem associated with the recommender systems. You will gain hands-on experience in information filtering, working on systems with zero historical data to refer to, as in the case of launching a new product. You will gain proficiency in working with personalized applications like movies, books, songs, news and such other recommendations. This project includes the following:
Project 2 – Recommendation for Movie, Summary
This is real world project that gives you hands-on experience in working with a movie recommender system. Depending on what movies are liked by a particular user, you will be in a position to provider data-driven recommendations. This project involves understanding recommender systems, information filtering, predicting ‘rating’, learning about user ‘preference’ and so on. You will exclusively work on data related to user details, movie details and others. The main components of the project include the following:
Project 1: – Python Web Scraping for Data Science
In this project you will be introduced to the process of web scraping using Python. It involves installation of Beautiful Soup, web scraping libraries, working on common data and page format on the web, learning the important kinds of objects, Navigable String, deploying the searching tree, navigation options, parser, search tree, searching by CSS class, list, function and keyword argument.
Intellipaat offers in-depth learning in python for data science. Python is one of the top programming languages that can be deployed in the domain of Data Science. You will learn about Python for machine learning, Hadoop streaming and also Python packages like Scikit and Scipy. Upon successful completion of the course you will be awarded the Intellipaat Python Certification.
You will be working on real time projects that have high relevance in the corporate world, step by step assignments and curriculum designed by industry experts. Upon completion of the training course you can apply for some of the best jobs in top MNCs around the world at top salaries. Intellipaat offers lifetime access to videos, course materials, 24/7 Support, and course material upgrading to latest version at no extra fees. Hence it is clearly a one-time investment.
Intellipaat basically offers the self-paced training and online instructor-led training. Apart from that we also provide corporate training for enterprises. All our trainers come with over 12 years of industry experience in relevant technologies and also they are subject matter experts working as consultants. You can check about the quality of our trainers in the sample videos provided.
If you have any queries you can contact our 24/7 dedicated support to raise a ticket. We provide you email support and solution to your queries. If the query is not resolved by email we can arrange for a one-on-one session with our trainers. The best part is that you can contact Intellipaat even after completion of training to get support and assistance. There is also no limit on the number of queries you can raise when it comes to doubt clearance and query resolution.
The Intellipaat self-paced training is for people who want to learn at their own leisurely pace. As part of this program we provide you with one-on-one sessions, doubt clearance over email, 24/7 Live Support, lifetime LMS and upgrade to the latest version at no extra cost. The prices of self-paced training can be 75% lesser than online training. While studying should you face any unexpected challenges then we shall arrange a Virtual LIVE session with the trainer.
We provide you with the opportunity to work on real world projects wherein you can apply your knowledge and skills that you acquired through our training. We have multiple projects that thoroughly test your skills and knowledge of various aspect and components making you perfectly industry-ready. These projects could be in exciting and challenging fields like banking, insurance, retail, social networking, ecommerce, marketing, sales, high technology and so on. The Intellipaat projects are equivalent to six months of relevant experience in the corporate world.
Yes, Intellipaat does provide you with placement assistance. We have tie-ups with 80+ organizations including Ericsson, Cisco, Cognizant, TCS, among others that are looking for skilled & quality professionals and we would be happy to assist you with the process of preparing yourself for the interview and the job.
Yes, if you would want to upgrade from the self-paced training to instructor-led training then you can easily do so by paying the difference of the fees amount and joining the next batch of classes which shall be separately notified to you.
Upon successful completion of training you have to take a set of quizzes, complete the projects and upon review and on scoring over 60% marks in the qualifying quiz the official Intellipaat verified certificate is awarded.
The Intellipaat Certification is a seal of approval and is highly recognized in 80+ corporations around the world including many in the Fortune 500 list of companies.
This course is designed for clearing Intellipaat Python Certification.As part of this 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 training program there will be a quiz that perfectly reflects the type of questions asked in the certification exam and helps you score better marks in certification exam.
The certification will be awarded on the completion of Project work (on expert review)(upon expert review) and on scoring of at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.
You will get Lifetime access to high quality interactive tutorials along with life time access to complete Course Material .There will be 24/7 access to video tutorials with email support. If you stuck in any unexpected problem we will provide online interactive sessions with trainer for issue resolving.
We provide 24X7 support by email for issues or doubts clearance for Self-paced training.
In online Instructor led training, trainer will be available to help you out with your queries regarding the course. If required, the support team can also provide you live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock.
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