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
Course Fees
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20+
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25+

Data Science Jobs in Auckland

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

  • 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 Auckland
Data Science This curriculum prepares you to work in a variety of Data Science professions and earn top-dollar wages. To find trends and patterns, use algorithms and modules. Today's Data Scientists must possess a wide range of abilities, including the ability to work with large amounts of data, parse that data, and translate it into an easily comprehensible format from which business insights may be drawn. 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. 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. . The Data Science Process, Communicating with Stakeholders, Software Engineering Practices, Object-Oriented Programming, Web Development, ETL Pipelines, Natural Language Processing, Machine Learning Pipelines, Experiment Design, Statistical Concerns of Experimentation, A/B Testing, and Introduction to Recommendation Engines are some of the topics covered in. You'll have a personal mentor who will keep track of your development. 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. Effectively analyze both organized and unstructured data Create strategies to address company issues.

List of All Courses & Internship by TechnoMaster

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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 Auckland

  • RIBSoftware | Location details: Level 3/19 Great South Road, Epsom, Auckland 1051, New Zealand | Classification: Software company, Software company | Visit Online: itwocostx.com | Contact Number (Helpline): +64 9 309 2026
  • FrontierSoftware | Location details: 87 Grafton Road, Grafton, Auckland 1010, New Zealand | Classification: Software company, Software company | Visit Online: frontiersoftware.com | Contact Number (Helpline): +64 9 373 5191
  • MissionReady | Location details: Level 5/115 Queen Street, Auckland CBD, Auckland 1010, New Zealand | Classification: Educational institution, Educational institution | Visit Online: missionreadyhq.com | Contact Number (Helpline): +64 800 005 875
  • NextMinute | Location details: 60 Broadway, Newmarket, Auckland 1023, New Zealand | Classification: Software company, Software company | Visit Online: nextminute.com | Contact Number (Helpline): +64 508 639 864
  • HughesJuddAccountingLtd | Location details: 112 Verran Road, Birkenhead, Auckland 0626, New Zealand | Classification: Certified public accountant, Certified public accountant | Visit Online: hughesjuddaccounting.co.nz | Contact Number (Helpline): +64 9 927 0207
  • Yuri&Neil?CRO&SEOStrategy | Location details: 101 Pakenham Street West, Auckland CBD, Auckland 1010, New Zealand | Classification: Market researcher, Market researcher | Visit Online: yuriandneil.co.nz | Contact Number (Helpline): +64 22 689 3394
  • SEBDATA | Location details: 149 Parnell Road, Parnell, Auckland 1052, New Zealand | Classification: Software company, Software company | Visit Online: sebdata.com | Contact Number (Helpline): +64 9 366 0789
  • IndustryConnect | Location details: B3/34 Triton Drive, Rosedale, Auckland 0632, New Zealand | Classification: Software training institute, Software training institute | Visit Online: industryconnect.org | Contact Number (Helpline): +64 800 100 081
  • InformationTechnologyTrainingInstitute(ITTI) | Location details: 3 Wakefield Street, Auckland CBD, Auckland 1010, New Zealand | Classification: Computer training school, Computer training school | Visit Online: | Contact Number (Helpline): +64 800 568 348
  • AGIEducationLimited. | Location details: Level 6 & 7/3 City Road, Grafton, Auckland 1010, New Zealand | Classification: Educational institution, Educational institution | Visit Online: agi.ac.nz | Contact Number (Helpline): +64 9 379 6628
  • Pos&EftposSpecialist|RocketPOSNZ| | Location details: 4 Cain Road, Penrose, Auckland 1061, New Zealand | Classification: EFTPOS equipment supplier, EFTPOS equipment supplier | Visit Online: rocketpos.co.nz | Contact Number (Helpline): +64 9 302 0919
  • ILXGroupNewZealand | Location details: 41 Shortland Street, Auckland CBD, Auckland 1010, New Zealand | Classification: Training centre, Training centre | Visit Online: ilxgroup.com | Contact Number (Helpline): +64 9 363 9777
  • TheInductionCompany | Location details: 5 Dockside Lane, Auckland CBD, Auckland 1010, New Zealand | Classification: Software company, Software company | Visit Online: inductionapp.co | Contact Number (Helpline): +64 9 520 5810
  • PlanitTesting | Location details: 11/125 Queen Street, Auckland CBD, Auckland 1010, New Zealand | Classification: Software company, Software company | Visit Online: planittesting.com | Contact Number (Helpline): +64 9 306 0690
  • SPMAssets | Location details: Building 2/1 Antares Place, Mairangi Bay, Auckland 0632, New Zealand | Classification: Software company, Software company | Visit Online: spmassets.com | Contact Number (Helpline): +64 9 921 4070
  • AIIT | Location details: Level 3/25-27 Crowhurst Street, Newmarket, Auckland 1023, New Zealand | Classification: Software training institute, Software training institute | Visit Online: aiit.ac.nz | Contact Number (Helpline): +64 9 889 5884
 courses in Auckland
This call refers back to the abundance of herbal resources, strategic vantage points, portage routes, and mahinga kai which first attracted Māori, after which different settlers. It is primarily based totally at the strategic route set through the 2012 Auckland Plan and: outlines what may be constructed in which affords for a compact city form describes the way to keep the agricultural and freshwater and marine environments. Auckland is the principle gateway inside and out of New Zealand, with the biggest and maximum energetic global airport, biggest global sea port and a crucial freight distribution function. Infrastructure Significant infrastructure tendencies considering that 2018 include: of of entirety of the Panmure to Pakuranga phase of the Eastern Busway and Puhinui Rail Station interchange of of entirety of Te Paataka Koorero o Takaanini (Community Hub and Library) the waterfront redevelopment the Urban Cycleways Programme rollout graduation of Central Interceptor work. This 30-yr plan units out Māori aspirations and effects, and it offers route to the Board to prioritise its Schedule of Issues of Significance and moves for Māori. Tūpuna Maunga o Tāmaki Makaurau Authority The Tūpuna Maunga o Tāmaki Makaurau Authority became hooked up in 2014 to co-govern 14 tūpuna maunga. Most migrants to New Zealand pick out to settle in Auckland due to the huge variety of employment and industrial possibilities. In massive component that is due to its outstandingly lovely herbal surroundings and the way of life possibilities it offers. It additionally allows Auckland Council to deal with moves for Māori effects and act according with te Tiriti o Waitangi/the Treaty of Waitangi. It contemplated the position of mana whenua in Auckland and signalled a change withinside the manner that mana whenua and Auckland Council companion in choice-making.

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