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

Modules

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

Demonstrations

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.

Certificate

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.