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 Colorado Springs

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

  • 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 Colorado Springs
Data Analytics Here are some common components of a data analytics course:. Work on real-world projects, participate in online competitions (such as Kaggle), and continue learning to enhance your skills. These courses are offered by various educational institutions, including universities, online platforms, and specialized training providers. Data analytics training involves acquiring the knowledge and skills needed to analyze and interpret data to make informed business decisions. 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.

List of All Courses & Internship by TechnoMaster

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List of Training Institutes / Companies in Colorado Springs

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 courses in Colorado Springs
By December 1, 2016, the District will broaden a plan to successfully tailor college-primarily based totally offerings which are supportive of the wishes of college students with a purpose to lower behavioral problems that show up in college and to boom college students` cap potential to enjoy the gaining knowledge of surroundings. By August 1, 2016, all District colleges would require and make certain that college personnel rent more than a few corrective measures earlier than referring a scholar to disciplinary government except it is able to be documented that the protection of college students and/or personnel is threatened or the conduct in query is such that the disruption to the academic surroundings can most effective be remedied via way of means of any such referral. As defined in extra element below, the District is dedicated to running with college students who show off conduct troubles to make certain that the scholars stay engaged withinside the District`s academic application and are given each possibility to attain their academic potential. In addition, the District commenced enforcing education on Positive Behavioral Interventions and Supports (“PBIS”) in numerous colleges. To that end, the District is dedicated to making sure that, to the most volume possible, its scholar subject regulations and methods are designed and applied in any such manner as to make certain that disciplinary sanctions do now no longer encompass the lack of academic education time for any college students, besides in the ones instances wherein it's far vital to make certain the on the spot protection of college students and personnel or while it's far the most effective method of making sure that scholar misbehavior does now no longer extensively intrude with the shipping of tutorial education to others. The Discipline Supervisor will be liable for making sure that the implementation of the District`s regulations regarding subject is truthful and equitable. If OCR has any objections to the plan submitted via way of means of the District for evaluation, OCR will notify the District of its objections promptly, no later than 60 days after receiving the draft plan. (e) By September 1, 2016, September 1, 2017, and September 1, 2018, the District will offer documentation to OCR concerning its implementation of the notice necessities of object 1(a), and documentation concerning its implementation of 1(b), and (c), such as the identification of the professional(s) it has consulted with and/or retained, the enter acquired via way of means of the professional(s), any similarly deliberate examinations and/or determinations regarding the foundation motive(s) of the racial disparity withinside the subject of college students, and the ensuing modifications made via way of means of the District. Designation of Responsible Employee/Collaboration with Experts 1. Throughout the route of this Agreement, the District will post for OCR evaluation and approval any modifications to the plan permitted via way of means of OCR previous to their implementation.

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