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 Quebec

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

  • 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 Quebec
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. 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. To find trends and patterns, use algorithms and modules. Identify and collect data from data sources. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. This curriculum prepares you to work in a variety of Data Science professions and earn top-dollar wages. Effectively analyze both organized and unstructured data Create strategies to address company issues. 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 Quebec. 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.

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 Quebec

  • Infonuagix | Location details: 870 de la, Rue de la Bruyère, Saint-Rémi, Quebec J0L 2L0 | Classification: Computer training school, Computer training school | Visit Online: | Contact Number (Helpline): (514) 942-4431
  • ITChapter | Location details: 204 Saint-Sacrement St #300, Montreal, Quebec H2Y 1W8, Canada | Classification: Computer consultant, Computer consultant | Visit Online: itchapter.com | Contact Number (Helpline): +1 877-770-6699
  • JaangaInc. | Location details: 220 Pine Ave W, Montreal, Quebec H2W 1R9, Canada | Classification: Software training institute, Software training institute | Visit Online: jaanga.ca | Contact Number (Helpline): +1 514-607-6108
  • ConcordiaUniversityDepartmentOfComputerScienceAndSoftwareEngineering | Location details: 2155 Guy St, Montreal, Quebec H3H 2L9, Canada | Classification: University, University | Visit Online: concordia.ca | Contact Number (Helpline):
  • Gologic | Location details: 5605 de, Av. de Gaspé #704, Montreal, Quebec H2T 2A4, Canada | Classification: Software company, Software company | Visit Online: gologic.ca | Contact Number (Helpline): +1 438-385-7188
  • NGSolutionsInc | Location details: 400 Bd du Curé-Labelle Bureau 401, Laval, Quebec H7V 2S7, Canada | Classification: Software training institute, Software training institute | Visit Online: | Contact Number (Helpline): +1 514-659-3313
  • FusionBPOServices-CallCenterServicesCanada | Location details: 507 Place d'Armes #1000, Montreal, Quebec H2Y 2W8, Canada | Classification: BPO company, BPO company | Visit Online: fusionbposervices.com | Contact Number (Helpline): +1 866-581-0038
  • McGillUniversity | Location details: 845 Sherbrooke St W, Montreal, Quebec H3A 0G4, Canada | Classification: University, University | Visit Online: mcgill.ca | Contact Number (Helpline): +1 514-398-4455
  • McGillFacultyOfEducation | Location details: 3700 Mc Tavish St, Montreal, Quebec H3A 1Y2, Canada | Classification: University, University | Visit Online: mcgill.ca | Contact Number (Helpline): +1 514-398-7042
  • PACCAdultEducationCentreAndVocationalTraining | Location details: 8300 George St, Lasalle, Quebec H8P 1E5, Canada | Classification: Adult education school, Adult education school | Visit Online: lbpce.ca | Contact Number (Helpline): +1 514-798-5588
  • ConcordiaUniversityDepartmentOfComputerScienceAndSoftwareEngineering | Location details: 2155 Guy St, Montreal, Quebec H3H 2L9 | Classification: University, University | Visit Online: concordia.ca | Contact Number (Helpline):
  • MatrixCollegeOfManagementTechnologyAndHealthcareInc | Location details: 1980, Rue Sherbrooke Ouest, Bur. 609 et 709, Montreal, Quebec H3H 1E3, Canada | Classification: Educational institution, Educational institution | Visit Online: matrixcollege.ca | Contact Number (Helpline): +1 514-934-4777
  • Microsoft | Location details: 2000 McGill College Ave, Montreal, Quebec H3A 3H3 | Classification: Software company, Software company | Visit Online: microsoft.com | Contact Number (Helpline): (514) 846-5800
  • LavalUniversity | Location details: 2325 Rue de l'Université, Québec, QC G1V 0A6 | Classification: University, University | Visit Online: ulaval.ca | Contact Number (Helpline): (418) 656-2131
  • CollègeCDI-Québec | Location details: 905 Boulevard Honoré-Mercier bur. 20, Québec City, Quebec G1R 5M6 | Classification: Educational institution, Educational institution | Visit Online: collegecdi.ca | Contact Number (Helpline): +1 800-251-6621
  • HerzingCollegeMontreal | Location details: 1616 René-Lévesque Blvd W, Montreal, Quebec H3H 1P8, Canada | Classification: College, College | Visit Online: herzing.ca | Contact Number (Helpline): +1 514-935-7494
 courses in Quebec
 In their pedagogic exercise, educators have innovated of their use of tests and withinside the accessibility and use of assist sources for instruction. The Government of Québec intends to make certain a more potent presence at the Canadian level via way of means of the use of the structural and important method at its disposal. For a complete description of the statistics and strategies used for evaluation on this record, see record Annex A: Data Sources and Methods. We may even introduce new tools to higher fill the gap of Canadian members of the family. The progress that we've made together, in Québec and in Canada, can handiest inspire us to outline not unusualplace goals. We are Quebecers, and that is our manner of being Canadian.  Within training, innovation depth is best in better training, with secondary and number one training about same. By ensuring that Québec`s particular traits are respected, differential remedy will become a manner to make certain same remedy for all of the provinces. Québec calls on all residents and federative companions to start a brand new talk. The ties binding Quebecers to different Canadians aren't simply governmental or institutional—they additionally join people and civil society, forming a basis for a genuine talk approximately the destiny of our country.

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