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Data Science - Syllabus, Fees & Duration

MODULE 1

  • The Data Science Process
  • Apply the CRISP-DM process to business applications
  • Wrangle, explore, and analyze a dataset
  • Apply machine learning for prediction
  • Apply statistics for descriptive and inferential understanding
  • Draw conclusions that motivate others to act on your results

MODULE 2

  • Communicating with Stakeholders
  • Implement best practices in sharing your code and written summaries
  • Learn what makes a great data science blog
  • Learn how to create your ideas with the data science community

MODULE 3

  • Software Engineering Practices
  • Write clean, modular, and well-documented code
  • Refactor code for efficiency
  • Create unit tests to test programs
  • Write useful programs in multiple scripts
  • Track actions and results of processes with logging
  • Conduct and receive code reviews

MODULE 4

  • Object Oriented Programming
  • Understand when to use object oriented programming
  • Build and use classes
  • Understand magic methods
  • Write programs that include multiple classes, and follow good code structure
  • Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  • Portfolio Exercise: Build your own Python package

MODULE 5

  • Web Development
  • Learn about the components of a web app
  • Build a web application that uses Flask, Plotly, and the Bootstrap framework
  • Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application

MODULE 6

  • ETL Pipelines
  • Understand what ETL pipelines are
  • Access and combine data from CSV, JSON, logs, APIs, and databases
  • Standardize encodings and columns
  • Normalize data and create dummy variables
  • Handle outliers, missing values, and duplicated data
  • Engineer new features by running calculations • Build a SQLite database to store cleaned data

MODULE 7

  • Natural Language Processing
  • Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  • Use scikit-learn to transform and vectorize text data
  • Build features with bag of words and tf-idf
  • Extract features with tools such as named entity recognition and part of speech tagging
  • Build an NLP model to perform sentiment analysis

MODULE 8

  • Machine Learning Pipelines
  • Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process
  • Chain data transformations and an estimator with scikit- learn’s Pipeline
  • Use feature unions to perform steps in parallel and create more complex workflows
  • Grid search over pipeline to optimize parameters for entire workflow
  • Complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset

MODULE 9

  • Experiment Design
  • Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  • Defining control and test conditions
  • Choosing control and testing groups

MODULE 10

  • Statistical Concerns of Experimentation
  • Applications of statistics in the real world
  • Establishing key metrics
  • SMART experiments: Specific, Measurable, Actionable, Realistic, Timely

MODULE 11

  • A/B Testing
  • How it works and its limitations
  • Sources of Bias: Novelty and Recency Effects
  • Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  • Portfolio Exercise: Using a technical screener from Starbucks to analyze the results of an experiment and write up your findings

MODULE 12

  • Introduction to Recommendation Engines
  • Distinguish between common techniques for creating recommendation engines including knowledge based, content based, and collaborative filtering based methods.
  • Implement each of these techniques in python.
  • List business goals associated with recommendation engines, and be able to recognize which of these goals are most easily met with existing recommendation techniques.

MODULE 13

  • Matrix Factorization for Recommendations
  • Understand the pitfalls of traditional methods and pitfalls of measuring the influence of recommendation engines under traditional regression and classification techniques.
  • Create recommendation engines using matrix factorization and FunkSVD
  • Interpret the results of matrix factorization to better understand latent features of customer data
  • Determine common pitfalls of recommendation engines like the cold start problem and difficulties associated with usual tactics for assessing the effectiveness of recommendation engines using usual techniques, and potential solutions.

Download Syllabus - Data Science
Course Fees
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20+
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25+

Data Science Jobs in Kanpur

Enjoy the demand

Find jobs related to Data Science in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Kanpur, chennai and europe countries. You can find many jobs for freshers related to the job positions in Kanpur.

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Storyteller
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Database Administrator
  • ML Engineer
  • Computer Vision Engineer

Data Science Internship/Course Details

Data Science internship jobs in Kanpur
Data Science Identify and collect data from data sources. Cleaning and validating data to ensure that it is accurate and consistent. The top Data Science course online for professionals who wish to expand their knowledge base and start a career in this industry is NESTSOFT in Kanpur. There are numerous reasons why you should take this course. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. Create data strategies with the help of team members and leaders. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. A Data Scientist is a highly skilled someone with advanced mathematical, statistical, scientific, analytical, and technical abilities who can prepare, clean, and validate organized and unstructured data for industries to utilize in making better decisions. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. To find trends and patterns, use algorithms and modules.

List of All Courses & Internship by TechnoMaster

Success Stories

The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Kanpur

  • EtahFireStation | Location details: Aligarh - Kanpur Rd, Police Line, Etah, Uttar Pradesh 207001, India | Classification: Fire station, Fire station | Visit Online: | Contact Number (Helpline): +91 94544 18496
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  • IndiaPostNaveenNagar | Location details: Shop Number. 117/209, Kakadav Rd, Navin Nagar, Kakadeo, near Om Chouraha, Kanpur, Uttar Pradesh 208025, India | Classification: Post office, Post office | Visit Online: indiapost.gov.in | Contact Number (Helpline): +91 512 250 1390
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  • SiSTech(Android&IOSDevelopment/DigitalMarketing/PHPDevelopment/BIGDATA) | Location details: 41, Lakhanpur, Housing Society, Vikas Nagar, Kanpur, Uttar Pradesh 208024, India | Classification: Software company, Software company | Visit Online: sistech.in | Contact Number (Helpline): +91 98398 93078
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  • MdtproWebDesigningCompany | Location details: Keshavpuram, Kalyanpur, Kanpur, Uttar Pradesh 208017, India | Classification: Website designer, Website designer | Visit Online: mdtpro.co.in | Contact Number (Helpline):
  • W3Karigar-WebsiteDesigningCompanyInPatna|WebDesignerDevelopmentCompanyInPatnaBihar | Location details: Dopulwa, Purandarpur, Jakkanpur, Gardanibagh, Patna, Bihar 800001, India | Classification: Website designer, Website designer | Visit Online: w3karigar.com | Contact Number (Helpline): +91 89693 66500
  • FahimabadPostOffice | Location details: FAHIMA BAAD DAAK KHANA, FAHIMABAD, Colonelganj, Kanpur, Uttar Pradesh 208001, India | Classification: Post office, Post office | Visit Online: indiapost.gov.in | Contact Number (Helpline): +91 512 254 6598
  • IndiaPostOffice | Location details: Govind Nagar, Kanpur, Uttar Pradesh 208006, India | Classification: Post office, Post office | Visit Online: indiapost.gov.in | Contact Number (Helpline): +91 1800 11 2011
  • RelianceJioOffice | Location details: Brajlaxmi Mansion, Ground Floor Shop No 2, 13, Sahdeo Mahto Marg, Mauza Dhakanpura, Patna, Bihar 800001, India | Classification: Telecommunications service provider, Telecommunications service provider | Visit Online: jio.com | Contact Number (Helpline): +91 612 254 0169
  • DigiBask-SoftwareDevelopmentAndITTrainingInKanpur | Location details: Ground Floor -171AB, Sharda Nagar, Kanpur, Uttar Pradesh 208025, India | Classification: Software company, Software company | Visit Online: digibask.com | Contact Number (Helpline):
 courses in Kanpur
It affords a very top situation of geographical research, mainly as Kanpur today, is a quick developing metropolis, function of city improvement in India* This thesis at the city geography of Kanpur indicates first of all, the geographical elements which have been directly or circuitously beneficial to the improvement of this city concentration; then strains the evolution of the townscape and the adjustments at the web website online for the duration of the past. In Kanpur Nagar, facts become accrued from 1,796 households, 1,901 girls, and 309 guys. become canvassed withinside the Woman`s Schedule. W. because of its beneficial scenario and relevant role in admire of the extraordinarily fertile, nicely irrigated and maximum populous vicinity of the Upper G-anga Plain. P. He is deeply indebted additionally through the assist he acquired from his wife. Thus the riverside strip of organization and flat floor at the steep excessive financial institution, near the nevigable channel of the Ganga become taken into consideration a beneficial web website online for Kanpur. In the II Chapter, the evolution and increase of the townscape had been mentioned with unique connection with the adjustments and trends after the Mutiny of 1857. The paintings has been primarily based totally upon non-public series of information and facts from the neighborhood reassets withinside the metropolis, supplimented through connection with statistics and facts where those are available.

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