data science using python - digitalvidya.com · spark, apache storm, kafka, mongodb. rohit kumar...

Data Science using

[Since 2009]

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Training partner for

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[Since 2009]

In exclusive association with

26,500+ Participants | 10,000+ Brands | 1900+ Trainings | 55+ Countries

Training Partner for

Python

Salient Features

Anyone with Programming Knowledge

Course Highlights

Govt. of India(Vskills Certified Course)

3 Hrs/Week Live Instructor-Led Online Sessions

Lifetime Access toUpdated Content and

Videos

Industry andAcademia Faculty

3 Weeks of Project Work

Internal Competitions with Prizes

Active Q/A Forum

Placement Support

Class Labs/Home Assignment (10 hours/Week Learning Time)

Individual Attention to Each Learner

Industry’s TopPython Advisors

Top PythonTools Covered

Industry Relevant Curriculum Hands-on Approach Money Back GuaranteeCareer Mentoring

This Course is for

Course Advisors and Instructors

Course Advisors

Ajay OhriData Scientist

Ajay Ohri is a Data Scientist and Blogger in an open source data science. Since 2007, he has published his blog DecisionStats.com.

Shweta GuptaVice President, Tech.

Shweta Gupta has 19+ years of Technology Leadership experience. She holds a patent and number of publications in ACM, IEEE and IBM journals like Redbook and developerWorks.

Manas Garg heads the Analytics for Marketing at Paypal. He takes Data Driven Decisions for Marketing Success.

Vishal is a Technology Influencer and CEO of Right Relevance. (A platform used by millions for content & influencer discovery)

Manas GargArchitect

Vishal MishraCEO & Co-Founder


Course Advisors

Course Instructors

Ajay OhriData Scientist

Ajay Ohri is a Data Scientist and Blogger in an open source data science. Since 2007, he has published his blog DecisionStats.com.


Shweta Gupta has 19+ years of Technology Leadership experience. She holds a patent and number of publications in ACM, IEEE and IBM journals like Redbook and developerWorks.

Manas Garg heads the Analytics for Marketing at Paypal. He takes Data Driven Decisions for Marketing Success.

Vishal is a Technology Influencer and CEO of Right Relevance. (A platform used by millions for content & influencer discovery)

Manas GargArchitect

Vishal MishraCEO & Co-Founder

Rohit Kumar is a Big Data Researcher with publications in many prestigious international conferences. He has 6 plus years experience in industry and expertise in various pro-gramming languages including Java, Scala, C++, Python, and Haskel. He works in variety of different database systems such as MySQL, Microsoft SQL, and Oracle Coher-ence and in many Big Data systems like Hadoop, Apache Spark, Apache Storm, Kafka, MongoDB.

Shweta GuptaVice President, Tech.Pritesh SrivastavaData Analyst (Contractor)


Vaishali GargLead Trainer, Data Analytics

Vaishali Garg is a self-taught data analyst with a health-care background. She use Python with Pandas, Numpy, Matplotlib and Scikit. She has keen interest in data analysis using Pandas and is actively answer Pandas related ques-tions on StackOverflow (Vaishaligarg, alias: A-Za-z). Some of her analysis is available on Kaggle.





Rohit KumarResearch Assistant, ULB




Shaheer Ahmed KhanResearcher

Shaheer is a Data Analytics professional, currently working for Laboratoire d’informatique de Grenoble, a leading research laboratory of informatics in France. His deep learn-ing for perception makes hime a perfect Data Analytics pro-fessional. He holds expertise in Data Mining, Machine Learning, Information Retrieval, Concurrent and Distributed Systems, Web Programming and Advance Programming.



Pritesh SrivastavaData Analyst (Contractor)

Pritesh is a Data Science enthusiast with an ability to turn data into actionable insights and meaningful stories. He possesses solid knowledge and hands-on experience of both quantitative/qualitative analysisand data mining. He is proficient in Python, Teradata SQL, deep learning, web auto-mation and ETL tools. He also has exposure towards applied machine learning - enjoys working with Data, creat-ing models, predictions and finding insights.Apart from his profession, he loves to travel and also procures his passion in Dramatics, Story-telling and Martial Arts.

Python Programming

Introduction to the Basics of Python Programming

OperatorsData TypesLoops: while & forConditionals: if-elseFunctions: Defining Functions, Anonymous Functions

Scientific Computing with Python - Numerical Python (NumPy)Importance of NumpyArray CreationData TypesUnary OperationsShape Manipulation -Reshape, Transpose, RavelArray Indexing

Boolean IndexingBroadcastingUniversal FunctionsMatrix MultiplicationStatistical Methods -Stacking -SplittingCopies and Views

Introduction to Data Analytics

Introduction to Data AnalyticsAn Overview Session for the Data Analyst, Data ScientistGetting Started with Jupyter NotebookIntroduction to the Open Data Science Learning and Competitive Platforms

An introduction topic to understand the drivers to data analytics field and its ecosystem.

In-depth understaing of Python Data Types, Functions and NumPy Arrays that come in handy while analysing data using Pandas.

The Python course is thoughtfully designed to allow learners with programming background to make a transition into the analytics industry with the correct skillsets using Python programmng language. It is designed in a way that the student starts with the introduction to Python programming, and in a very hands-on learning method using Jupyter Notebook, will learn the libraries of Data Analytics using Numpy, Pandas, with applied statistics and machine learning concepts and applications. Post completion of the program, learners will be prepared to device solutions for real time problems in the industry.

Course Curriculum

Introduction to Pandas

Data Analysis Workflow in Python using Pandas

Pandas Data Structures -Series & Data FrameBasic Functions on Data FrameIndexing & Selecting Data -Selection by Level -Selection by Position -Boolean SelectionGroup By: Split-Apply- Combine

Learn Pandas - a Python library that provides high-performance, easy-to-use data structures and data analysis tools.

Handling Missing DataMerging Multiple DatasetsData Analysis Scenarios

Data Visualization

Time Series Analysis

Simple & Multi-line Plots, Multiple Figures Creating Different Types of Plots using Matplotlib and SeabornSimple Plot with X and Y Axis

Linestyles and ColorMutiple Lines on Same PlotControlling Line PropertiesAdding Lables, Gridlines, AnnotationsX and Y Ticks and RotationsSplinesLegendsWorking with Multiple Figures and AxesShare X and Y AxisAdding Subplots

Merging of Data FrameReshaping: Stack, Unstack, Pivot, MeltDummy/Indicator VariablesWorking with Text DataExtract Using Regular Expression (Regex)Pattern Matching in StringsData Loading and File FormatsLoading JSON FilesXML and HTML Web ScrapingInteracting with HTML and Web APIsWorking with DatabasesEncoding & Handling C Parse Errors

Converting Series to Time SeriesHandling Invalid DataEpoch / Date-Time IndexIndexingTime/Date ComponentsPeriod & Period IndexHandling Time ZonesParsing & Manipulating Dates

Creating Different Types of PlotsLine GraphsBar PlotsHistogramsBox PlotStacked PlotsScatter PlotPie Chart

Data Visualization using Matplotlib and Seaborn. Creating different types of plots with single or multiple lines, multiple figures and axes.

Advanced Data Analysis using Pandas

Healthcare domain: Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain. This capstone project focus on EEG data analysis, giving an opportunity for students to learn through complexities in dealing with such complex real-world data. It will make a very interested data analytics applications as this data arises from a large study to examine EEG correlates of genetic predisposition to alcoholism. There were two groups of subjects: alcoholic and control and each subject was exposed to a single or two stimuli which were pictures of objects chosen from the 1980 Snodgrass and Vanderwart picture set, and capturing their reactions.

Applied Statistics and Machine Learning

Introduction and StatisticsWhat is Machine LearningMachine Learning Real World ExampleStatisticsBias and VarianceCovariance and CorrelationsStandard DeviationsProbabilityScikit-learn

Model Evaluation and Parameters Tuning

Example of the kind of course-end assignments are

Cross ValidationGrid SearchEvaluation Metrics & ScoringOverfitting and UnderfittingIntroductionExamplesGuidelines

Data PreprocessingLoading Datasets

Data CleansingEncoding Data

Feature SelectionWorking with Text Data

Split Train and Test DataTypes of ML Algorithms

Supervised Learning IntroductionUnsupervised Learning Introduction

Supervised Learning AlgorithmsLinear Regression

Logistic RegressionKNN

Supervised Learning Algorithms continuedNaïve Bayes

Decision TreeRandom Forest

SVMUnsupervised Learning

K-MeansHierarchical Clustering

This section will introduce the students to the machine learning concepts, and then dive into the sci-kit library. It will cover the supervised algorithms like regression, KNN, Randon Forest etc, and unsupervised learning using K-means. It will also take the students through model evaluation and tuning.

Capstone Projects (3 Weeks)

The Capstone project are created to offer complex problems to students so that they can experience an integrated experience of the complete Data Science problem solving, end to end. The approach to this project is to think, define, design, code, test and tune your solution, in such a way that students apply all aspects of the data analytics process.

Our Course Participants Work at

The Placement Process

Tools Covered

Placement ServicesWe partner with 10+ organizations who directly source their Data Analytics manpower needs from us. From resume creation to helping you crack the final interview, our dedicated place-ment team is always on toes to connect talent with the right opportunity.

The Candidates resume is refined and polished as per Market Standards to help them be search-able.

The Candidates are prepared for an initial quiz and a coding test.

Finally, the candidates are prepared for the final round of interview.

The Resume is shared with relevant organisations by our

placement team.

Natural Language Processing: This is one of the most applied areas for AI, Data Science, and ML. The real world is filled with text data, and it is usually messy hence cleaning and handling text is an important step towards making smarter Machine Learning algorithms. Using one such dataset from the movie domain, you will apply the most common concepts of NLP. This project will empower the learners to build intermediate skills in the natural language processing domain, and empower them to start building up on all the latest technol-ogy advancements.

Duration Fee Batch Options

Rs. 34,900+GST Weekend18 Weeks

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Interested? Contact Us!

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Attend a Free Orientation Session: http://www.digitalvidya.com/data-analytics-course

- Naresh Mehta AVP – Data Science & Analytics ,

-Ajay Ohri Data Scientist,

“ ”Good to see Digital Vidya becoming increasingly more involved in covering data science vertical, look forward to collaborate with DV to help shape this industry.

“ ”Yes, I like the huge investment Digital Vidya is doing to create the next generation of talent. Initial feedback suggests Digital Vidya produces high-quality Data Analysts.

Industry Experts Speak

-Madhu Vadlamani Lead Analytics,

“ ”I can see a good course structure and well-designed syllabus for those who are passionate enough to enter into the analytics world. The platform helps people grow professionally and in very less time.

rthis Speak

What Makes us Proud?

-Vani Ananthamurthy(Business Operations Senior Analyst, Accenture)

“ ”I was looking for customized content and I found the same in Digital Vidya. Content is structured and well planned. Classes were very interactive and trainer’s presentation skills were very good. People who are new to the subject can also understand clearly. Thank you so much!

-Nanddeep Nasnodkar (Sr. Software Developer - Remote Software Solutions)

“ ”This course gets you started from very basics, makes you think and solve the assignments, and suddenly you find yourself doing Data Analytics all by yourself!

data science using python - digitalvidya.com · spark, apache storm, kafka, mongodb. rohit kumar...

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