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Python for Data Science Fresno Certification Training

  • At JanBask Training, become a master of Python programming around Data Analysis, Data Deep Learning, Machine Learning, Data Visualization & NLP via real-case assignments led Data Science with Python Fresno Training Program.
  • Learn Python to qualify the Data Science in Python Fresno certifications and become an integral part of growth-prone Data Science roles.

Learn Python programming around Data Science to unlock great career opportunities!

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Why Data Science in Python Fresno certifications?

Here are the few reasons why recruiters and job markets are looking for certified Data Scientists with Python:

#1

Data Science in Python Fresno is the most demanding IT skill.

Job Market

The US leads the Data Science job market, requiring 190,000 Data Scientists using Python by next year.

Salesforce Growth

You Should Join Our Classes If You Are:

  • Just starting off & aren’t sure where to start from
  • In an established role but need to dive deep
  • Looking to brush up your skills & master the course
  • Willing to get better in your current or new job

$16B

Data Science industry is expected to touch US$ 16 billion by 2025.

Average Salary

The average salary for a Mid-Career Data Scientist with Python is $106,010. (Payscale).

Thriving Career Opportunities - What and Where!

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Get all the technical skills to help businesses transform their big data!

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IT

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Retail

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Manufacturing / Medicine

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Banking &
Finance

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Construction

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Communication & media

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Manufacturing

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Energy/utility

Big data Engineer

Data Scientist

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Sr. Data Engineer

Instructor-led Live Online Data Science with Python Classes


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Data Science in Python Training Course Roadmap

Scroll through the Data Science in Python Syllabus that you will be learning ahead.

Data science with Python

    • What is analytics & Data Science?
    • Common Terms in Analytics
    • Analytics vs. Data warehousing, OLAP, MIS Reporting
    • Relevance in industry
    • Types of problems and business objectives in various industries
    • How leading companies are harnessing the power of analytics?
    • Critical success drivers
    • Overview of analytics tools & their popularity
    • Analytics Methodology & problem solving framework
    • List of steps in Analytics projects
    • Identify the most appropriate solution design for the given problem statement
    • Project plan for Analytics project & key milestones based on effort estimates
    • Build Resource plan for analytics project
    • Why Python for data science?
    • Overview of Python- Starting with Python

Oops & Python

    • Installation of Python
    • Python Editors & IDE's(Canopy, pycharm, Jupyter, Rodeo, Ipython etc…)
    • Understand Jupyter notebook & Customize Settings
    • Concept of Packages/Libraries - Important packages(NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc)
    • Installing & loading Packages & Name Spaces
    • Python programming language
    • Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
    • List and Dictionary Comprehensions
    • Variable & Value Labels – Date & Time Values
    • Basic Operations - Mathematical - string - date
    • Anaconda Python distribution
    • Reading and writing data
    • operators, Loop & conditional statements
    • Debugging & Code profiling
    • How to create classes and modules and how to call them?
    • Hands-on Assignment, Real Scenarios, MCQs, Practice Tests on Python

Statistics & Probability

    • Brief to Statistics
    • Statistical and Non-statistical Analysis
    • Major Categories of Statistics
    • Measures of Central Tendencies and Variance
    • Probability Distributions
    • Normal distribution
    • Central Limit Theorem
    • Statistical Analysis Considerations
    • Population and Sample
    • Statistical Analysis Process
    • Data Distribution
    • Dispersion
    • Histogram
    • Correlation and Inferential Statistics

Manipulating Data

    • What is a data Manipulation. Using Pandas library
    • Numpy dependency of Pandas library
    • Series object in pandas
    • Dataframe in Pandas
    • Loading and handling data with Pandas
    • How to merge data objects
    • Concatenation and various types of joins on data objects, exploring dataset
    • Manipulating DataCleansing Data with Python
    • Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting etc)
    • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
    • Python Built-in Functions (Text, numeric, date, utility functions)
    • Python User Defined Functions
    • Stripping out extraneous information

Python using Machine Learning

    • Machine Learning & Predictive Modelling
    • Data Pre-processing, Sampling, Model Building, Validation
    • Feature engineering & dimension reduction
    • Concept of optimization & cost function
    • Overview of gradient descent algorithm
    • K-Means Clustering, Hierarchical Clustering, Spectral Clustering
    • Decision Trees, Types of Decision Tree Algorithms
    • Bagging,Random forest, Boosting
    • Neural Networks and Its Applications
    • Neural Networks for Regression & Classification
    • Support Vector Regression & classifier
    • KNN For solving regression problems
    • Applications of Naïve Bayes in Classifications

Time Series forecasting & Data visualization with Matplotlib

    • What is Time Series Analysis?
    • Time series data, Steps of forecasting
    • Components of time series data
    • Scatter plot, Time Plot, and Lag Plot
    • Visualization principles
    • Naive forecast methods
    • Errors in forecast and its metrics
    • Model-Based approaches
    • Data-driven approach to forecasting
    • Smoothing techniques
    • Moving Average
    • Exponential Smoothing
    • Holts / Double Exponential Smoothing
    • De-seasoning and de-trending
    • Overview to Matplotlib
    • Matplotlib for plotting graphs and charts

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Python For Data Science Training Fresno Corporate Training

Data Science in Python Fresno Corporate Training

Train your workforce with new-age technologies and a cutting-edge curriculum with Data Science in Python Fresno Corporate Training to help them understand & communicate with data better.

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Experience Our Data Science with Python Certification Training Journey!

  • Introduce yourself to the concepts, principles and working knowledge of Data Science with Python
  • Understand the real world scenarios with real-time job oriented projects and case studies
  • Learn from World Class Trainers who are one amongst the top rated working IT Professionals
  • Clear your certifications while we make you ready for the huge job market present out there

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