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Python automation
Engineering

Python Automation Engineering

Our Data Analytics with Python and SQL course is part of our comprehensive IT curriculum. We employ a unique six-step process that sets us apart from other boot camps nationwide, ensuring our students receive personalized, industry-specific training that prepares them to thrive in the evolving world of technology.

Course Structure Overview

Student Dashboard

We provide an individual dashboard for each and every student of ours. It will help you track down all of your classes, materials and progress.

Online Live Classes

You can attend our data analytics class online in your own comfort. The classes will be live. You can engage efficiently during online classes.

Recording of the Classes

If you miss out on anything during our data analytics online training, you can easily access our recorded classes and keep up with the rest.

Resume Building

An organized resume can easily get you your targeted job. Our data analytics training online classes will assist you to build a standard job resume.

Interview Preparation

An interview is a gateway to getting a job. It is very crucial for landing a good job. Transfotech will also help you prepare for your interview.

Easy Enrollment

This online program of ours is very easy to register for. Your desired job is just a few clicks away.

Download Course Curriculum

What you will learn by doing the course

Data analysts with skills in Python and SQL are in high demand, with opportunities growing rapidly across industries. Learn data analytics online to unlock the power of data-driven decision-making and become a valuable asset in today’s data-centric world.

  • Build a solid foundation in data analytics principles and understand how to make data-driven decisions that support business goals.
  • Learn to harness Python for data manipulation, analysis, and visualization, enabling you to extract insights from complex datasets.
  • Master SQL for data retrieval and management, working with databases to organize, access, and analyze structured data efficiently.
  • Develop essential skills in cleaning, organizing, and preparing data, ensuring accuracy and reliability for analysis.
  • Create impactful visualizations that help communicate data insights clearly, using libraries like Matplotlib and Seaborn.
  • Practice EDA techniques to uncover patterns, trends, and relationships within data, leading to valuable business insights.
  • Apply statistical methods to analyze data distributions, correlations, and hypotheses, supporting data-driven decision-making.
  • Gain hands-on experience through projects that mirror real industry challenges, allowing you to apply your skills in practical scenarios.
  • Stay informed about the latest trends and best practices in data analytics, enhancing your competitive edge in the field.

Details about the course

  1. Introduction to Data Analytics
  2. Responsibilities of a Data Analyst
  3. The Data Ecosystem
  4. Spreadsheet Basics – Part 1
  5. Spreadsheet Basics – Part 2
  6. Analyzing Data Using Spreadsheets
  7. Career path in Data analytics and prospects with python
  8. What do Employers look for in a Data Analyst
  1. Data Visualization and Dashboards
  2. Using Visualizations to Tell a Data Story
  3. Creating Basic Charts in Excel (Line, Pie, and Bar Charts)
  1. Overview of SQL and its importance in data science
  2. Creating databases and tables
  3. Inserting data into tables, import data
  4. SELECT queries and Filtering rows (where, and, or , not, like)
  5. Querying Multiple Tables with JOINS
  6. Understanding table relationships
  7. INNER JOIN, LEFT JOIN, RIGHT JOIN
  8. Using aliases for table names
  1. Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
  2. Grouping data with GROUP BY and Having
  3. ROW_NUMBER(), RANK(), DENSE_RANK()
  4. Understanding PARTITION BY and ORDER BY clauses
  5. Common Table Expressions (CTEs)
  6. Bulk operations with BULK INSERT and BULK DELETE
  1. Automation Testing Basic, Tools, Technology
  2. Installation (Python, IDE, Selenium)
  3. Your first Python program: Hello World!
  4. Basic syntax: variables, operators, and expressions
  1. Conditional statements: if, else-if
  2. Loop: for, while, break, continue
  3. Problem Solving Fibonacci Sequence
  4. Problem Solving Prime Number
  1. Introduction to arrays, tuple, list, dictionary
  2. Method, parameters and return type
  3. Problem Solving : Range or prime number
  1. Introduction to Object-Oriented Programming (OOP)
  2. Classes and Objects
  3. Constructor
  4. OOP Principals
  5. Creating classes
  1. File Handling
  2. Python Libraries
  3. Numpy
  4. Pandas
  5. Loading data from csv, Excel and SQL
  1. Extracting Stock Data Using a Python Library
  2. Intro to Web Scraping Using BeautifulSoup
  3. Analyzing Historical Stock
  1. Using libraries such as Pandas, Numpy and Scipy
  2. Develop Python code for cleaning and preparing data for
    analysis
  3. Missing values, formatting, normalizing, and binning data
  4. Exploratory data analysis and apply analytical techniques
  5. Manipulate data using dataframes, summarize data
  6. Understand data distribution, perform correlation and
    create data pipelines
  1. Python libraries: Matplotlib, Seaborn, and Folium
  2. Create different types of charts: line, area, histograms, bar,
    pie, box, scatter, and bubble
  3. Create advanced visualizations: waffle charts, word
    clouds, regression plots, maps with markers, & choropleth
    maps
  4. Power BI & Tableau
  1. Introduction to Machine learning
  2. Data distribution
  3. Training dataset and Test Dataset concept
  4. Creating Model
  5. Training model
  6. Predicting with Model
  7. Advance concept of ML (NLP, Machine Learning, Deep
    Learning)

Course Instructor

Quality Assurance Training Classes in Manhattan, New York

Zakir Hossain

Professor

International American University (IAU), LA, USA

An experienced software engineer and educator, Zakir has introduced QA Engineering at International American University and teaches Quality Assurance at Transfotech Academy. Skilled in .NET Core, SQL, and AngularJS, he focuses on impactful solutions and guiding future tech leaders.

Feedback from our students

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What is in this course

  • Data analytics overview
  • Data visualization with Excel
  • SQL basic
  • Python Programming
  • Web Crawling with Python
  • Python Library for Data Analytics
  • Data visualization with Python
  • Machine learning overview with Python

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