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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Data Science Jobs in Edmonton

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

  • 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 Edmonton
Data Science To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. . 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. 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. To find trends and patterns, use algorithms and modules. 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. 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. 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 Edmonton. You may learn all of the skills and talents required to become a data scientist by enrolling in the top data science online courses in Edmonton. 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.

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 Edmonton

  • ReevesCollege-EdmontonCityCentre | Location details: 10004 Jasper Ave #500, Edmonton, AB T5J 1R3 | Classification: Educational institution, Educational institution | Visit Online: reevescollege.ca | Contact Number (Helpline): +1 800-269-7095
  • NorthernAlbertaInstituteOfTechnology(NAIT) | Location details: 11762 106 St, Edmonton, AB T5G 2R1 | Classification: Polytechnic college, Polytechnic college | Visit Online: nait.ca | Contact Number (Helpline): (780) 471-6248
  • Coursetter | Location details: 1289 McAllister Way SW, Edmonton, AB T6W 0B1 | Classification: Management school, Management school | Visit Online: coursetter.ca | Contact Number (Helpline): (780) 887-4153
  • CanadianImperialCollege | Location details: 11525 23 Ave NW, Edmonton, AB T6J 4T3 | Classification: College, College | Visit Online: canadianimperial.ca | Contact Number (Helpline): +1 877-652-4547
  • ApprenticeshipAndIndustryTraining(AIT) | Location details: CAT 430, 11763 106 St, Edmonton, AB T5G 2R1 | Classification: Apprenticeship center, Apprenticeship center | Visit Online: tradesecrets.alberta.ca | Contact Number (Helpline): +1 800-248-4823
  • TheKing'sUniversity | Location details: 9125 50 St NW, Edmonton, AB T6B 2H3 | Classification: University, University | Visit Online: kingsu.ca | Contact Number (Helpline): (780) 465-3500
  • POWEREngineers | Location details: 9452 51 Ave NW, Edmonton, AB T6E 5A6 | Classification: Engineering consultant, Engineering consultant | Visit Online: powereng.com | Contact Number (Helpline): (780) 439-4003
  • RapidBoostMarketing | Location details: 9131 39 Ave NW Unit # 206, Edmonton, AB T6E 5Y2 | Classification: Internet marketing service, Internet marketing service | Visit Online: rapidboostmarketing.com | Contact Number (Helpline): (587) 413-1214
  • AcademyOfLearningCareerCollege-EdmontonWest | Location details: 17718 64 Ave NW, Edmonton, AB T5T 4J5 | Classification: College, College | Visit Online: myaolcc.com | Contact Number (Helpline): (780) 496-9428
  • TechnologyTrainingCentre | Location details: University of Alberta, Cameron Library, 85 Avenue Northwest B-11, Edmonton, AB T6G 2J8, Canada | Classification: Computer training school, Computer training school | Visit Online: ualberta.ca | Contact Number (Helpline): +1 780-492-1397
  • FacultyOfGraduateStudiesAndResearch | Location details: 2 29 Triffo Hall, Edmonton, AB T6G 2E1 | Classification: University department, University department | Visit Online: ualberta.ca | Contact Number (Helpline): +1 800-758-7136
  • NAIT | Location details: NAIT HP Centre, W203 Princess Elizabeth Ave NW, Edmonton, AB T5G 3K4 | Classification: University, University | Visit Online: nait.ca | Contact Number (Helpline):
  • AcademicInvest | Location details: 5730 Riverbend Rd NW, Edmonton, AB T6H 4T4 | Classification: Educational consultant, Educational consultant | Visit Online: academicinvest.com | Contact Number (Helpline): (780) 906-0014
  • SundanceCollege | Location details: 10115 100a St NW, Edmonton, AB T5J 2W2 | Classification: College, College | Visit Online: sundancecollege.com | Contact Number (Helpline): (587) 405-2020
  • NorQuestCollegeEdmontonCampus | Location details: 10215 108 St NW, Edmonton, AB T5J 1L6 | Classification: Community college, Community college | Visit Online: norquest.ca | Contact Number (Helpline): (780) 644-6000
  • OPCTrainingInstitute | Location details: 15614 116 Ave NW, Edmonton, AB T5M 3S5 | Classification: Computer training school, Computer training school | Visit Online: opcti.com | Contact Number (Helpline): (780) 784-4444
 courses in Edmonton
• Edmonton is one in all Canada s sunniest municipalities, with a median,299 hours of light according to time. moment, you could nevertheless detect the beaver, that's Canada s countrywide beast, abiding in Edmonton s swash vale. • Nearly 20 of Edmonton residers are foreign- born. • Edmonton has the stylish according to capita position of parkland of any Canadian megalopolis. concentrated in Edmonton. • Edmonton inaugurated a Waste- toBiofuels product installation in 2012 thru a cooperation among Enerkem and the City of Edmonton. • Edmonton s swash vale paperwork the longest stretch of affiliated megacity parkland in North America. 4 as of April 2013. • Edmonton has the nethermost property levies of any foremost Canadian megalopolis. • Edmonton is the primary crossroad factor for the Alberta mecca, an full- size channel contrivance lesser than kilometres in general length, which vessels maximum feedstocks, natural fueloline and hydrocarbon products.

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