Data Science Training by Experts

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Our Training Process

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
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Data Science Jobs in Hobart

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 Hobart, chennai and europe countries. You can find many jobs for freshers related to the job positions in Hobart.

  • 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 Hobart
Data Science Creative thinking, problem-solving skills, curiosity, and a drive to learn about and investigate industry trends and development, as well as teamwork, are among the soft skills required by data scientists. To find trends and patterns, use algorithms and modules. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. Exercises, tasks, and projects that are completed in real-time 24 hours a day, 7 days a week, A large network of like-minded newbies, an industry-recognized intellipaat credential, and individualized employment support Several data scientist responsibilities are listed below. Create data strategies with the help of team members and leaders. Data Science provides a diverse set of tools for analyzing data from a range of sources, including financial records, multimedia files, marketing forms, sensors, and text files. Identify and collect data from data sources. 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. There are numerous reasons why you should take this course. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills.

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 Hobart

  • TasmanianTrainingConsortium | Location details: Executive Building, 15 Murray St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: ttc.tas.gov.au | Contact Number (Helpline): +61 3 6232 7511
  • Getbusi | Location details: Level 1/61 Davey St, Hobart TAS 7000, Australia | Classification: Website designer, Website designer | Visit Online: getbusi.com | Contact Number (Helpline): +61 3 6165 1555
  • SkillsTasmania | Location details: 4 Salamanca Pl, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: skills.tas.gov.au | Contact Number (Helpline): +61 1800 655 846
  • TasmanianTrainingInstitute | Location details: 210/86 Murray St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: tastraining.com.au | Contact Number (Helpline): +61 414 404 685
  • TechHouseStudio | Location details: Level 1/252 Macquarie St, Hobart TAS 7000, Australia | Classification: Software company, Software company | Visit Online: techhousestudio.com.au | Contact Number (Helpline): +61 420 787 140
  • NDATasmania | Location details: Trafalgar Centre, 110 Collins St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: nda.com.au | Contact Number (Helpline): +61 3 6224 2660
  • NDATasmania | Location details: Trafalgar Centre, 110 Collins St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: nda.com.au | Contact Number (Helpline): +61 3 6224 2660
  • NationalInstituteOfEducationAndTechnology | Location details: Level 4/2-4 Kirksway Pl, Hobart TAS 7004, Australia | Classification: School, School | Visit Online: niet.edu.au | Contact Number (Helpline): +61 3 6281 0009
  • UniversityOfTasmania | Location details: Churchill Ave, Hobart TAS 7005, Australia | Classification: University, University | Visit Online: utas.edu.au | Contact Number (Helpline): +61 3 6226 2999
  • STEPSEducation&Training | Location details: Ground Floor, 27 Elizabeth St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: stepsgroup.com.au | Contact Number (Helpline): +61 3 6213 5200
  • TasCollege | Location details: Unit 1, Level 1/86 Collins St, Hobart TAS 7000, Australia | Classification: College, College | Visit Online: tascollege.edu.au | Contact Number (Helpline): +61 3 6295 5296
  • DigitalVisionDesigns | Location details: 6 Lefroy St, North Hobart TAS 7000, Australia | Classification: Software company, Software company | Visit Online: dvdesigns.com.au | Contact Number (Helpline): +61 3 6231 4183
  • GovernmentEducationAndTrainingInternational | Location details: 26 Bathurst St, Hobart TAS 7000, Australia | Classification: Educational institution, Educational institution | Visit Online: study.tas.gov.au | Contact Number (Helpline): +61 3 6165 5727
  • PrincipalComputers | Location details: 243 Harrington St, Hobart TAS 7000, Australia | Classification: Computer store, Computer store | Visit Online: principalcomputers.com.au | Contact Number (Helpline): +61 3 6235 5010
  • TasTAFE | Location details: 75 Campbell St, Hobart TAS 7000, Australia | Classification: Vocational school, Vocational school | Visit Online: tastafe.tas.edu.au | Contact Number (Helpline): +61 1300 655 307
  • NDATasmania | Location details: Trafalgar Centre, 110 Collins St, Hobart TAS 7000, Australia | Classification: Training centre, Training centre | Visit Online: nda.com.au | Contact Number (Helpline): +61 3 6224 2660
 courses in Hobart
A community vision to guide strategic planning ensures that the council's work is relevant to what Hobart people want for their city. Our ancestors planned generations into the future. We are proud of where we are: identity, unique and lasting connections to people and places, shared happiness, comfort and contentment. Community Vision TEN YEAR CAPITAL STRATEGIC PLAN FOUR YEAR PRODUCTION PLAN ANNUAL PLAN ANNUAL DISTRIBUTION AND UNITS PLAN does not directly affect the life of the city; Many aspects of the vision touch on issues such as creativity and disaster preparedness, which apply to various people and industries. Our ancestors lived in countries. The vision is for Hobart City Local Government Area , but it is a capital city. Our connection to this earth is a feeling that is hard to describe, but it is a feeling that we can all relate to. Their way of life was sustainable. This document is a community view of our city: Hobart, Tasmania. It does not talk about special policies, budgets or projects.

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