The Data Scientist’s Toolbox: Techniques and Strategies for Success & Leveling Up Your Analytical Skills (Bootcamp)

Key Outcomes

Python’s scope is nearly limitless. Data scientists, engineers, and developers are flocking to Python because it is versatile for applications ranging from web development to data science and from artificial intelligence to cybersecurity. In this program, you will learn the essentials of Python coding:

Identify, interpret, and apply core programming building blocks in Python code.
Use algorithmic thinking to break up problems into smaller pieces and solve each piece individually.
Recognize and apply best industry practices for programming.
Interpret, use, and build on existing code and Python libraries.

Program Modules

Data Science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This bootcamp will help anyone interested in pursuing a career in data science by teaching them fundamental skills to get started in this in-demand field.

The bootcamp consists of 8 weeks of live online courses that will provide you with the foundational skills required for Data Science, including open-source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. You’ll learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.

Upon successfully completing these courses, you will have the practical knowledge and experience to delve deeper in Data Science and work on more advanced Data Science projects.

Training Intro: Advance Data Analytics using SQL, Python, Statistics, Power BI and Tableau (Bootcamp)

A brief outline of the certificate:

• 6 hours per week for a 2 months duration

• Automated assessments and quizzes

• Repeat unlimited times at no additional cost

• Verified and Certified certificate

• 24×7 support to answer your queries and doubts

• Capstone project

• Resume/Interview preparation & Job placement assistance


  • Module 1: Writing Your First Program
    Interpret and write code using variables
    Recognize error messages in Python code
    Demonstrate understanding of Python’s core syntax rules
    Translate simple algorithms to Python functions
  • Module 2: Programming with Basic Logical Structures
    Recognize and use basic data operators on Boolean
    Interpret and write the correct syntax for conditionals
    Recognize, interpret, and write programs with conditionals
    Recognize and interpret programs with multiple interacting functions
    Identify and solve programming errors through established debugging strategies
  • Module 3: Expanding Logical Structure with Iteration
    Recognize, interpret, and write programs using while loops and for loops
    Apply indexes and slices to strings and lists to access individual parts
    Recognize, interpret, and write programs that iterate through lists and strings with for loops
    Evaluate provided test sets and write new test sets to verify that code works as expected
  • Module 4: Deeper Applications of Iteration
    Recognize, interpret, and write programs with nested loops
    Recognize and interpret basic recursive functions
    Translate simple recursive algorithms to Python functions
  • Module 5: Applying Logic to Large Data Sets
    Interpret and write code using operators, functions, and methods on strings and lists
    Recognize and use common string and list methods
    Identify the differences between mutable and immutable data types
    Interpret documentation to find pre-existing methods that fulfill specific needs
  • Module 6: Algorithmic Thinking and Problem Solving
    Identify whether a problem can be solved by following an algorithm, applying a pattern
    Use top-down design to break up medium-sized programming tasks into smaller pieces, solving each piece individually
    Apply general style principles to write readable code
  • Module 7: Practical Approaches to Efficiency
    Express the efficiency of code snippets using well-established standards of abstraction
    Recognize differences in algorithmic approaches based on computational efficiency
    Identify differences in basic data structures, such as lists, sets, and dictionaries, based on computational efficiency
    Interpret and write code using operators, functions, and methods on sets and dictionaries
  • Module 8: Structuring Programs with Object-Oriented Programming
    Recognize object-oriented programming constructs, such as objects, classes, fields, and methods
    Correctly structure code using object-oriented programming constructs
  • Module 9: Using Python Libraries for Greater Productivity
    Interpret and write code that reads and writes data from files in the computer system
    Interpret and use components from the documentation of Python libraries
    Use online sources to find, compare, and install Python libraries
  • Module 10: Putting Things Together – Capstone Project
    Recognize best industry practices for writing and managing large programs. Write a medium-level program (300-500 lines) with some level of guidance

Program Experience

Office Hours with Learning Facilitators


Coding Exercises in Each Module

Bite-Sized Learning

Knowledge Checks

Dedicated Program Support Team

Mobile Learning App

Peer Discussion

Capstone Project

Bonus Content on Advanced Topics

Career Support

Certification & Digital Badge

Who Should Attend?

This online program is designed for anyone who is interested in acquiring programming skills in Python & Machine Learning. No prior programming knowledge is required.


Upon successful completion of the program, participants will receive a digital certificate of completion from American Institute for IT Professionals. This is a training program, and it is not eligible for academic credit.

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Course price


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