Data Analytics Training/Course by Experts

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Our Training Process

Data Analytics - Syllabus, Fees & Duration

  1. Learn Python Program from Scratch

    Programming is an increasingly important skill; this program will establish your proficiency in handling basic programming concepts. By the end of this program, you will understand object -oriented programming; basic programming concepts such as data types, variables, strings, loops, and functions; and software engineering using Python.
  2. Statistical and Mathematical Essential for Data Science

    Statistics is the science of assigning a probability through the collection, classification, and analysis of data. A foundational part of Data Science, this session will enable you to define statistics and essential terms related to it, explain measures of central tendency and dispersion, and comprehend skewness, correlation, regression, distribution. Understanding the data is the key to perform Exploratory Data analysis and justify your conclusion to the business or scientific problem.
  3. Data Science with Python

    Perform fundamental hands-on data analysis using the Jupyter Notebook and PyCharm based lab environment and create your own Data Science projects learn the essential concepts of Python programming and gain in-depth knowledge in data analytics, Machine Learning, data visualization, web scraping, and natural language processing. Python is a required skill for many Data Science positions.
  4. Database

    A database is an organized collection of structured information, or data, typically stored electronically in a computer system. A database is usually controlled by a database management system (DBMS). Company data are store in databases and later on retrieved using python to develop analytics and bring insights to business problems.
  5. Machine Learning

    It will make you an expert in Machine Learning, a subclass of Artificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will master Machine Learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for your role with advanced Machine Learning knowledge.
  6. Data Analytics with R:

    The Data Science with R enables you to take your data science skills to solve multiple problems with statistical and related libraries. The course makes you skilled with data wrangling, data exploration, data visualization, predictive analytics, and descriptive analytics techniques. You will learn about R from basics with installation to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.
  7. Visualization with Tableau

    Data Science with Tableau helps to see and understand data solving various business problems. Our visual analytics platform is transforming the way people use data to solve problems. C ourse enables you to create visualizations, organize data, and design plots and develop dashboards to bring more insights to the problem. Learn various concepts of Data Visualization, combo charts, working with filters, parameters, and sets, and building interactive dashboards.
  8. Visualization with Power BI

    This Power BI deals with how to handle multiple data sources, extract them perform various data filtering, manipulations, understanding the patterns in data and create customized dashboards with powerful developer tools It is suitable for business intelligence (BI) and reporting professionals, data analysts, and professionals working with data in any sector.

Technologies Training:

  • Python:

    Introduction to Python and Computer Programming, Data Types, Variables, Basic Input -Output Operations, Basic Operators, Boolean Values, Conditional Execution, Loops, Lists and List Processing, Logical and Bitwise Operations, Functions, Tuples, Dictionaries, Sets, and Data Processing, Modules, Packages, String and List Methods, and Exceptions, File Handlings. Regular expressions, the Object - Oriented Approach: Classes, Methods, Objects, and the Standard Objective Features; Exception Handling, and Working with Files.
  • R:

    R Introduction, Data Inputting in R, Strings,Vectors, Lists, Matrices, Arrays Functions and Programming in R, Data manipulation in R, Factors, DataFrame, Packages, Data Shaping, R-Data Interfa ce, Web Dataand Database, Charts-Pie, Bar Charts, Boxplots, Histograms, LineGraphs, Mean, Median and Mode, Regression- Linear, Multiple, Logistic, Poisson, Distribution-Normal, Binomial, Analysis-Covariance, Time Series, Survival, Nonlinear Least Square, DecisionTree, Random Forestc
  • MySQL

    MySQL – Introduction, Installation, Create Database, Drop Database, Selecting Database, Data Types, Create Tables, Drop Tables, Insert Query, Select Query, WHERE Clause, Update Query, DELETE Query, LIKE Clause, Sorting Results, Using Joins, Handling NULL Values, ALTER Command, Aggregate functions, MySQL Clauses, MySQL Conditions.
  • Matplotlib:

    Scatter plot, Bar charts, histogram, Stack charts, Legend title Style, Figures and subplots, Plotting function in pandas, Labelling and arranging figures, Save plots.
  • Seaborn:

    Style functions, Color palettes, Distribution plots, Categorical plots, Regression plots, Axis grid objects.
  • NumPy

    Creating NumPy arrays, Indexing and slicing in NumPy, Downloading and parsing data Creating multidimensional arrays, NumPy Data types, Array attributes, Indexing and Slicing, Creating array views copies, Manipulating array shapes I/O.
  • Pandas:

    Using multilevel series, Series and Data Frames, Grouping, aggregating, Merge Data Frames, Generate summary tables, Group data into logical pieces, manipulate dates, Creating metrics for analysis, Data wrangling, Merging and joining, Data Mugging using Pandas, Building a Predictive Mode.
  • Scikit-learn:

    Scikit Learn Overview, Plotting a graph, Identifying features and labels, Saving and opening a model, Classification, Train / test split, What is KNN? What is SVM?, Linear regression , Logistic vs linear regression, KMeans, Neural networks, Overfitting and underfitting, Backpropagation, Cost function and gradient descent, CNNs
  • Tableau

    Tableau Architecture, File Types, Data Types, Tableau Operator, String Functions, Date Functions Logical Functions, Aggregate Functions, Joins in Tableau, Types of Tableau Data Source, Data Extracts, Filters, Sorting, Formatting, Adding Worksheets and Renaming Worksheet In Tableau, Tableau Save, Reorder and Delete Worksheet, Charts, dashboard.
  • Power BI

    Power BI Architecture, Components, Power BI Desktop, Connect to Data in Power BI Desktop, Data Sources for Power BI, DAX in Power BI, Q & A in Power BI, Filters in Power BI, Power BI Query Overview, Creating and Using Measures in Power, Calculated Columns, Data Visualizations, Charts, Area, Funnel, Combo, Donut, Waterfall, Line, Maps, Bar, KPI, Power BI Dashboard .

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Data Analytics Jobs in Vancouver

Enjoy the demand

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

  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist
  • Data Engineer
  • Quantitative Analyst
  • Market Research Analyst
  • Operations Analyst
  • Healthcare Analyst
  • Supply Chain Analyst
  • Fraud Analyst

Data Analytics Internship/Course Details

Data Analytics internship jobs in Vancouver
Data Analytics Here are some common components of a data analytics course:. These courses are offered by various educational institutions, including universities, online platforms, and specialized training providers. Work on real-world projects, participate in online competitions (such as Kaggle), and continue learning to enhance your skills. The content of data analytics courses can vary, but they typically cover a range of topics related to collecting, analyzing, and interpreting data to extract valuable insights. Here is a step-by-step guide to help you get started with data analytics training: Remember that practice is essential in data analytics. A data analytics course is an educational program designed to teach individuals the skills and knowledge needed to work in the field of data analytics. Data analytics training involves acquiring the knowledge and skills needed to analyze and interpret data to make informed business 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 Vancouver

  • RapidComputerTraining,Inc. | Location details: 777 Hornby St #600, Vancouver, BC V6Z 1S4 | Classification: Computer training school, Computer training school | Visit Online: rapidtraining.ca | Contact Number (Helpline): +1 888-376-2981
  • On-TrackCorporateTraining | Location details: 609 Granville St Suite 650, Vancouver, BC V6C 1X6 | Classification: Training centre, Training centre | Visit Online: on-track.com | Contact Number (Helpline): (604) 683-0020
  • Thinkific | Location details: 369 Terminal Ave #400, Vancouver, BC V6A 4C4 | Classification: Software company, Software company | Visit Online: thinkific.com | Contact Number (Helpline): +1 888-832-2409
  • ILAC-InternationalLanguageAcademyOfCanada | Location details: 688 W Hastings St, Vancouver, BC V6B 1P1 | Classification: Language school, Language school | Visit Online: ilac.com | Contact Number (Helpline): (604) 484-6660
  • Trainerize | Location details: 1250 Homer St, Vancouver, BC V6B 2Y5 | Classification: Software company, Software company | Visit Online: trainerize.com | Contact Number (Helpline):
  • BayswaterVancouver(FormerlyELSVancouver) | Location details: 549 Howe St 6th Floor, Vancouver, BC V6C 2C2 | Classification: Language school, Language school | Visit Online: bayswater.ac | Contact Number (Helpline): (604) 684-9577
  • SterlingCollege | Location details: 1111 Melville St Suite 200, Vancouver, BC V6E 3V6 | Classification: Educational institution, Educational institution | Visit Online: sterlingcollege.ca | Contact Number (Helpline): (604) 638-7040
  • LangaraCollegeContinuingStudies:WestBroadwayCampus | Location details: 601 W Broadway, Vancouver, BC V5Z 4C2 | Classification: Community college, Community college | Visit Online: langara.ca | Contact Number (Helpline): (604) 323-5322
  • AshtonCollege | Location details: 1190 Melville St #300, Vancouver, BC V6E 3W1 | Classification: College, College | Visit Online: ashtoncollege.ca | Contact Number (Helpline): (604) 899-0803
  • LangaraCollege | Location details: 100 W 49th Ave, Vancouver, BC V5Y 2Z6 | Classification: College, College | Visit Online: langara.ca | Contact Number (Helpline): (604) 323-5511
  • UBCExtendedLearning | Location details: 5950 University Blvd, Vancouver, BC V6T 1Z3 | Classification: Educational institution, Educational institution | Visit Online: extendedlearning.ubc.ca | Contact Number (Helpline): (604) 822-1444
  • VCC-DowntownCampus | Location details: 250 W Pender St, Vancouver, BC V6B 1S9 | Classification: College, College | Visit Online: vcc.ca | Contact Number (Helpline): (604) 871-7000
  • LangaraCollege | Location details: 100 W 49th Ave, Vancouver, BC V5Y 2Z6 | Classification: College, College | Visit Online: langara.ca | Contact Number (Helpline): (604) 323-5511
 courses in Vancouver
In 2011, over forty% of Metro Vancouver`s populace spoke a mom tongue aside from one in all Canada`s legit languages (English and French). But considered via a greater stringent analytical lens Vancouver`s enjoy of boom and change discloses greater tricky aspects, fashioned each via way of means of modern-day elements in addition to a records of underdevelopment related to geographical marginality given that first European contact (1792). Factors that make a contribution to its excessive rating consist of the `west coast` way of life of outside dwelling and get right of entry to to inexperienced area, in addition to excessive rankings on infrastructure, education and culture. 33 biggest metropolitan location, after Toronto and Montreal (Metro Vancouver, 2016). forty six million withinside the wider agglomeration of `Metro Vancouver` this is made up of 21 municipalities1, Vancouver is Canada`s 0. Geographically, it's far bounded on all facets via way of means of some of boundaries. Our storyline recognizes the revolutionary control of area and territory withinside the large area, consisting of sustained investments in ecological, social and cultural amenity, and the cosmopolitan civility of the area`s groups and neighbourhoods. Of those forty%, the 5 maximum spoken languages were Chinese (languages combined), Punjabi, Tagalog (Filipino), Korean and Farsi (Duff and Becker-Zavas, 2017). On the only hand, it's far mentioned as one of the maximum suitable locations to stay globally, in terms of first-rate of lifestyles and livability indices. The 2016 census found out that “seen minorities” (“humans of colour”) make up the bulk of the populace in 5 Metro Vancouver municipalities consisting of Richmond, Burnaby and Surrey2 (Statistics Canada, 2016).

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